Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Systematic quantification of gene interactions by phenotypic array analysis.

John L Hartman1, Nicholas P Tippery

  • 1Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, WA 98109, USA. jhartman@fhcrc.org

Genome Biology
|July 9, 2004
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Lemnaceae and Orontiaceae Are Phylogenetically and Morphologically Distinct from Araceae.

Plants (Basel, Switzerland)·2021
Same author

University of Alabama at Birmingham Nathan Shock Center: comparative energetics of aging.

GeroScience·2021
Same author

A cell-nonautonomous mechanism of yeast chronological aging regulated by caloric restriction and one-carbon metabolism.

The Journal of biological chemistry·2020
Same author

High-resolution yeast quiescence profiling in human-like media reveals complex influences of auxotrophy and nutrient availability.

GeroScience·2020
Same author

Genetic diversity of native and introduced Phragmites (common reed) in Wisconsin.

Genetica·2020
Same author

Extensive interlineage hybridization in the predominantly clonal Hydrilla verticillata.

American journal of botany·2019
Same journal

Integrated lipidomic and transcriptomic profiling of the host response in human malaria.

Genome biology·2026
Same journal

Centromeric satellite expansion drives genome evolution in the snowy owl.

Genome biology·2026
Same journal

Mapping the landscape of allele-specific expression in porcine genomes.

Genome biology·2026
Same journal

Genomic sequence evolution underlying human neocortical interareal diversification.

Genome biology·2026
Same journal

Regulatory mechanisms driven by functional 3'-UTR variants in alcohol use disorder and related traits.

Genome biology·2026
Same journal

A longitudinal single-nucleus transcriptomic atlas of bovine placentation reveals dynamic cellular hierarchies and regulatory programs.

Genome biology·2026
See all related articles

This study developed a method to screen for gene interactions affecting cell growth, identifying networks involved in DNA repair and metabolism. The research provides a framework for analyzing gene interaction networks that buffer cellular growth.

Area of Science:

  • * Yeast genetics and chemical genomics
  • * Systems biology and network analysis

Background:

  • * Understanding gene interactions is crucial for deciphering cellular processes and buffering mechanisms.
  • * Previous methods lacked quantitative approaches for large-scale screening of gene-environment interactions.

Purpose of the Study:

  • * To develop and apply a quantitative phenotypic array method for screening gene-environment interactions in yeast.
  • * To identify gene networks that buffer cell growth against perturbations like hydroxyurea (HU).

Main Methods:

  • * Application of a phenotypic array method to haploid and homozygous diploid yeast deletion strain sets.
  • * Development of a growth index to screen for non-additive gene deletion and perturbation interactions.
  • * Genome-wide screening for hydroxyurea (HU) chemical-genetic interactions, followed by quantification and selectivity analysis.

Related Experiment Videos

Main Results:

  • * 298 haploid deletion strains showed significant chemical-genetic interactions with HU.
  • * Interactions were quantified across various HU concentrations and compared with other drug treatments.
  • * Bio-modules of genes with similar interaction profiles were identified, implicating DNA repair, protein secretion, and metabolic control.

Conclusions:

  • * The study presents a quantitative framework for analyzing gene interaction networks.
  • * Identified gene modules provide insights into cellular growth buffering mechanisms.
  • * The developed method enables large-scale discovery of functional gene networks.