Comparing maps of gene interactions offers insight into how yeast cells repair DNA damage. If you were on your way to a new country, you would pack a map to help you find the major cities, roads, and interesting places to explore. Recently, researchers have created similar maps to help them start unraveling the complex architecture of a cell. These maps are created by measuring genetic interactions, specifically the effect that a mutation in one gene has on the phenotype of a mutation in a second gene (see the figure). Using novel genetic tools for studying budding yeast (1) and automated technology, investigators can now systematically and rapidly measure these genetic interactions (epistasis) for all pairs in gene subsets of interest (about 400 to 800 genes). The resulting E-MAPs (epistasis miniarray profiles) (2) have helped chart interactions for a diverse array of cellular processes, including the early secretory pathway, chromosome function, signaling pathways, and RNA processing (3, 4). These E-MAPs, however, have all have been collected from cells grown under the same condition: in a rich growth medium. But just as a snowstorm can block some roads and force changes in traffic, changing environmental conditions can cause cells to rewire their genetic networks, necessitating the drawing of a new map. On page 1385 of this issue, Bandyopadhyay et al. (5) describe the creation of just such a condition-specific E-MAP and a novel method for analyzing it.
[1]
Sourav Bandyopadhyay,et al.
Rewiring of Genetic Networks in Response to DNA Damage
,
2010,
Science.
[2]
D. Koller,et al.
Automated identification of pathways from quantitative genetic interaction data
,
2010,
Molecular systems biology.
[3]
Nir Friedman,et al.
Modularity and directionality in genetic interaction maps
,
2010,
Bioinform..
[4]
Nevan J. Krogan,et al.
Quantitative Genetic Interactions Reveal Biological Modularity
,
2010,
Cell.
[5]
Gary D Bader,et al.
The Genetic Landscape of a Cell
,
2010,
Science.
[6]
B. Andrews,et al.
Systematic mapping of genetic interaction networks.
,
2009,
Annual review of genetics.
[7]
Maya Schuldiner,et al.
Explorations in topology-delving underneath the surface of genetic interaction maps.
,
2009,
Molecular bioSystems.
[8]
R. Shamir,et al.
From E-MAPs to module maps: dissecting quantitative genetic interactions using physical interactions
,
2008,
Molecular systems biology.
[9]
Trey Ideker,et al.
Integrating physical and genetic maps: from genomes to interaction networks
,
2007,
Nature Reviews Genetics.
[10]
Sean R. Collins,et al.
Exploration of the Function and Organization of the Yeast Early Secretory Pathway through an Epistatic Miniarray Profile
,
2005,
Cell.
[11]
Gary D Bader,et al.
Systematic Genetic Analysis with Ordered Arrays of Yeast Deletion Mutants
,
2001,
Science.