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Updated: Jun 4, 2025

Competitive Genomic Screens of Barcoded Yeast Libraries

Competitive Genomic Screens of Barcoded Yeast Libraries

Published on: August 11, 2011

Genome-wide conditional degron libraries for functional genomics.

Eduardo Gameiro¹, Karla A Juárez-Núñez¹, Jia Jun Fung¹

¹Institute of Molecular Biology , Mainz, Germany.

The Journal of Cell Biology

|December 18, 2024

Summary

This summary is machine-generated.

Researchers developed new conditional alleles for yeast functional genomics, enabling the study of essential genes and reducing errors from suppressor mutations. This advances the study of gene function in Saccharomyces cerevisiae.

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Area of Science:

Molecular Biology
Yeast Genetics

Background:

Functional genomics using knockout alleles is limited for essential genes and prone to suppressor mutations.
Existing methods can lead to inaccurate gene function annotations.

Purpose of the Study:

To overcome limitations of knockout alleles for functional genomics.
To create genome-wide conditional allele libraries for inducible protein degradation in yeast.
To improve the study of essential genes and reduce annotation errors.

Main Methods:

Constructed genome-wide libraries of conditional alleles using the auxin-inducible degron (AID) system in Saccharomyces cerevisiae.
Fused over 5,600 essential and non-essential proteins to a C-terminal AID tag.
Assessed protein degradation efficiency and identified limiting factors like protein abundance and tag accessibility.

Main Results:

Determined N-terminal tagging is more likely to impair protein function than C-terminal tagging.
Achieved approximately 90% degradation of AID-tagged proteins using 5-Ph-IAA.
Identified a role for GSF2 in hydroxyurea resistance through genome-wide screens.

Conclusions:

The developed AID system provides a powerful tool for conditional protein depletion in yeast.
These libraries enable functional studies of previously intractable essential genes.
The findings expand the yeast genetics toolbox for comprehensive functional genomics.