Modularity and directionality in genetic interaction maps
Open accessAbstract
MOTIVATION: Genetic interactions between genes reflect functional relationships caused by a wide range of molecular mechanisms. Large-scale genetic interaction assays lead to a wealth of information about the functional relations between genes. However, the vast number of observed interactions, along with experimental noise, makes the interpretation of such assays a major challenge. RESULTS: Here, we introduce a computational approach to organize genetic interactions and show that the bulk of observed interactions can be organized in a hierarchy of modules. Revealing this organization enables insights into the function of cellular machineries and highlights global properties of interaction maps. To gain further insight into the nature of these interactions, we integrated data from genetic screens under a wide range of conditions to reveal that more than a third of observed aggravating (i.e. synthetic sick/lethal) interactions are unidirectional, where one gene can buffer the effects of perturbing another gene but not vice versa. Furthermore, most modules of genes that have multiple aggravating interactions were found to be involved in such unidirectional interactions. We demonstrate that the identification of external stimuli that mimic the effect of specific gene knockouts provides insights into the role of individual modules in maintaining cellular integrity. AVAILABILITY: We designed a freely accessible web tool that includes all our findings, and is specifically intended to allow effective browsing of our results (http://compbio.cs.huji.ac.il/GIAnalysis). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Developing a multiscale representation requires analyzing communities in biological networks at more than one scale, defining and identifying communities at each scale, and tracing containment to infer a hierarchical map.
“Developing a multiscale representation requires analyzing communities in biological networks at more than one scale. Communities (clusters of highly interconnected nodes) are first defined and identified at each of multiple scales; subsequently, communities that are contained within other communities, in whole or in part, can be traced to infer a hierarchical map (Figure 2) (Dotan-Cohen et al., 20”
From Mapping the multiscale structure of biological systems (2021) · cites this paper as Jaimovich et al., 2010
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- Authors
- Jaimovich, A., Rinott, R., Schuldiner, M., Margalit, H., & Friedman, N.
- Affiliations
- Hebrew University of Jerusalem (IL)
- Corresponding author
- Schuldiner, Maya
- Margalit, Hanah
- Friedman, Nir
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-06-01
- Volume
- 26
- Issue
- 12
- Pages
- i228-i236
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC2881382
- OpenAlex
- W2105638592
- Cited by
- 32
- References
- 41
- Citations by year
- 2026: 1 · 2021: 2 · 2020: 2 · 2018: 1 · 2017: 3 · 2016: 4 · 2014: 3 · 2013: 3 · 2012: 2
- FWCI
- 2.09
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Bioinformatics (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- European Commission (LSHG-CT-2005-512028)
- National Institutes of Health (1r01ca119176-01)
- National Cancer Institute (1R01CA119176-01, R01-CA119176)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
- Keywords
- genetic interactions, modularity, synthetic lethality, gene function, genetic screen, network hierarchy, cell integrity, web-based tool
- MeSH terms
- Algorithms, Saccharomyces cerevisiae, Computational Biology, Saccharomyces cerevisiae Proteins, Gene Regulatory Networks
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