Quantitative analysis of fitness and genetic interactions in yeast on a genome scale

被引：141

作者：

Baryshnikova, Anastasia ^{[1
,2
]}

Costanzo, Michael ^{[1
]}

Kim, Yungil ^{[3
,4
]}

Ding, Huiming ^{[1
]}

Koh, Judice ^{[1
]}

Toufighi, Kiana ^{[1
]}

Youn, Ji-Young ^{[1
,2
]}

Ou, Jiongwen ^{[5
]}

San Luis, Bryan-Joseph ^{[1
]}

Bandyopadhyay, Sunayan ^{[3
]}

Hibbs, Matthew ^{[6
]}

Hess, David ^{[7
]}

Gingras, Anne-Claude ^{[8
]}

Bader, Gary D. ^{[1
,2
]}

Troyanskaya, Olga G. ^{[9
]}

Brown, Grant W. ^{[5
]}

Andrews, Brenda ^{[1
,2
]}

Boone, Charles ^{[1
,2
]}

Myers, Chad L. ^{[3
]}

机构：

[1] Univ Toronto, Banting & Best Dept Med Res, Terrence Donnelly Ctr Cellular & Biomol Res, Toronto, ON, Canada

[2] Univ Toronto, Terrence Donnelly Ctr Cellular & Biomol Res, Dept Mol Genet, Toronto, ON, Canada

[3] Univ Minnesota Twin Cities, Dept Comp Sci & Engn, Minneapolis, MN USA

[4] Univ Minnesota Twin Cities, Dept Elect & Comp Engn, Minneapolis, MN USA

[5] Univ Toronto, Dept Biochem, Terrence Donnelly Ctr Cellular & Biomol Res, Toronto, ON, Canada

[6] Jackson Lab, Bar Harbor, ME 04609 USA

[7] Santa Clara Univ, Dept Biol, Santa Clara, CA 95053 USA

[8] Mt Sinai Hosp, Samuel Lunenfeld Res Inst, Toronto, ON M5G 1X5, Canada

[9] Princeton Univ, Dept Comp Sci, Lewis Sigler Inst Integrat Genom, Carl Icahn Lab, Princeton, NJ 08544 USA

来源：

NATURE METHODS | 2010年 / 7卷 / 12期

基金：

加拿大健康研究院; 美国国家卫生研究院; 美国国家科学基金会;

关键词：

SACCHAROMYCES-CEREVISIAE; INTERACTION NETWORKS; EPISTASIS; PATHWAY; MAP; CONSERVATION; LANDSCAPE; RIM101; DFG16;

D O I：

10.1038/NMETH.1534

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Global quantitative analysis of genetic interactions is a powerful approach for deciphering the roles of genes and mapping functional relationships among pathways. Using colony size as a proxy for fitness, we developed a method for measuring fitness-based genetic interactions from high-density arrays of yeast double mutants generated by synthetic genetic array (SGA) analysis. We identified several experimental sources of systematic variation and developed normalization strategies to obtain accurate single-and double-mutant fitness measurements, which rival the accuracy of other high-resolution studies. We applied the SGA score to examine the relationship between physical and genetic interaction networks, and we found that positive genetic interactions connect across functionally distinct protein complexes revealing a network of genetic suppression among loss-of-function alleles.

引用

页码：1017 / U110

页数：9

共 40 条

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