The Genetic Landscape of a Cell

By M. Costanzo, Anastasia Baryshnikova, J. Bellay, Yungil Kim, Eric D. Spear, C. Sevier, Huiming Ding, Judice L. Y. Koh, Kiana Toufighi, Sara Mostafavi and 43 more. 2010

2,188 citations recorded by the source corpus.

Making Connections Genetic interaction profiles highlight cross-connections between bioprocesses, providing a global view of cellular pleiotropy, and enable the prediction of genetic network hubs. Costanzo et al. (p. 425) performed a pairwise fitness screen covering approximately one-third of all potential genetic interactions in yeast, examining 5.4 million gene-gene pairs and generating quantitative profiles for ∼75% of the genome. Of the pairwise interactions tested, about 3% of the genes investigated interact under the conditions tested. On the basis of these data, a reference map for the yeast genetic network was created. A genome-wide interaction map of yeast identifies genetic interactions, networks, and function. A genome-scale genetic interaction map was constructed by examining 5.4 million gene-gene pairs for synthetic genetic interactions, generating quantitative genetic interaction profiles for ~75% of all genes in the budding yeast, Saccharomyces cerevisiae. A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function. The global network identifies functional cross-connections between all bioprocesses, mapping a cellular wiring diagram of pleiotropy. Genetic interaction degree correlated with a number of different gene attributes, which may be informative about genetic network hubs in other organisms. We also demonstrate that extensive and unbiased mapping of the genetic landscape provides a key for interpretation of chemical-genetic interactions and drug target identification.

Subfields: Computational Theory and Mathematics, Molecular Biology

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Citations in the corpus

Systems genetics approaches to understand complex traits (2013, background): “The integration of systematic genetics with systems genetics has so far been used only in unicellular organisms 62,79,80 , but it should also be feasible in mammals using cultured cells.”
The BioGRID Interaction Database: 2011 update (2010, methodology): “The BioGRID processes large pre-publication data sets provided by authors for immediate release upon the publication date (2,7,20).”
Genes and growth performance in crustacean species : a review of relevant genomic studies in crustaceans and other taxa (2013, background): “Recent large-scale genetic analyses of model organisms have enabled systematic screening of epistatic interactions as well as the pleiotropic structure of the genotype-phenotype map and provide valuable insights into the functional organization of a eukaryotic cell (Costanzo et al. 2010; Wagner & Zh”
Using deep learning to model the hierarchical structure and function of a cell (2018, methodology): “Extensive training was made possible by an existing compendium of yeast growth phenotypes measured for single-and double-gene-deletion genotypes, comprising several million genotype–phenotype training examples 15,16 .”
Quantitative and logic modelling of gene and molecular networks (2015, background): “Gene and protein interaction networks have been reconstructed to obtain a comprehensive view of genome regulation 8,25–27 or to understand specific processes (for instance, the regulation of pluripotency) 28–31.”
Translation of Genotype to Phenotype by a Hierarchy of Cell Subsystems (2016, methodology): “Experimental Procedures Genetic interaction data Experimental genetic interaction scores for >6 million double mutants in yeast, measured using synthetic genetic arrays (Costanzo et al., 2010) (SGA, 1,711 queries × 3,885 arrays), Cell Syst.”
Differential network biology (2012, background): “Interestingly, DNA repair factors also form a rich cluster of interactions in static genetic networks (Collins et al , 2007; Costanzo et al , 2010) although they are not interaction ‘hubs’ as they are in the differential DNA damage network (Bandyopadhyay et al , 2010).”
BioPAX – A community standard for pathway data sharing (2010, neutral): “• Genetic interactions occur between two genes when the phenotypic consequence of perturbing both genes is different than expected given the phenotypes of each single gene perturbation 39 .”