ArticlePLoS genetics2009
Genome-wide association data reveal a global map of genetic interactions among protein complexes.
Article in PLoS genetics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- Extensive genetic interactions (epistasis) linked to alcohol use disorder in a high-risk population.Communications biology · 2026Article
- Discovering genetic interactions bridging pathways in genome-wide association studies.Nature communications · 2019Article
- High-Throughput Quantitative Genetic Interaction Mapping in the Fission YeastCold Spring Harbor protocols · 2018Article
- Solving the genetic puzzle of systemic lupus erythematosus.Pediatric nephrology (Berlin, Germany) · 2015Review
- The cancer cell map initiative: defining the hallmark networks of cancer.Molecular cell · 2015Review
- Integrated genomics identifies convergence of ankylosing spondylitis with global immune mediated disease pathways.Scientific reports · 2015Article
- Influence of Feature Encoding and Choice of Classifier on Disease Risk Prediction in Genome-Wide Association Studies.PloS one · 2015Article
- Co-regulated transcripts associated to cooperating eSNPs define Bi-fan motifs in human gene networks.PLoS genetics · 2014Article
- Fully automated protein complex prediction based on topological similarity and community structure.Proteome science · 2013Article
- Statistical analysis reveals co-expression patterns of many pairs of genes in yeast are jointly regulated by interacting loci.PLoS genetics · 2013Article
- Genetic variants and their interactions in disease risk prediction - machine learning and network perspectives.BioData mining · 2013Article
- A novel link prediction algorithm for reconstructing protein-protein interaction networks by topological similarity.Bioinformatics (Oxford, England) · 2013Article
- Article
- eQTL Epistasis - Challenges and Computational Approaches.Frontiers in genetics · 2013Article
- Article
- Discovering the hidden sub-network component in a ranked list of genes or proteins derived from genomic experiments.Nucleic acids research · 2012Article
- Integration of biological networks and pathways with genetic association studies.Human genetics · 2012Review
- SCS3 and YFT2 link transcription of phospholipid biosynthetic genes to ER stress and the UPR.PLoS genetics · 2012Article
- Leveraging models of cell regulation and GWAS data in integrative network-based association studies.Nature genetics · 2012Article
- Template-based protein structure modeling using the RaptorX web server.Nature protocols · 2012Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
This work demonstrates how gene association studies can be analyzed to map a global landscape of genetic interactions among protein complexes and pathways. Despite the immense potential of gene association studies, they have been challenging to analyze because most traits are complex, involving the combined effect of mutations at many different genes. Due to lack of statistical power, only the strongest single markers are typically identified. Here, we present an integrative approach that greatly increases power through marker clustering and projection of marker interactions within and across protein complexes. Applied to a recent gene association study in yeast, this approach identifies 2,023 genetic interactions which map to 208 functional interactions among protein complexes. We show that such interactions are analogous to interactions derived through reverse genetic screens and that they provide coverage in areas not yet tested by reverse genetic analysis. This work has the potential to transform gene association studies, by elevating the analysis from the level of individual markers to global maps of genetic interactions. As proof of principle, we use synthetic genetic screens to confirm numerous novel genetic interactions for the INO80 chromatin remodeling complex.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.