Epistasis—the essential role of gene interactions in the structure and evolution of genetic systems

By P. Phillips. Nature reviews genetics, 2008

1,535 citations recorded by the source corpus.

Epistasis, or interactions between genes, has long been recognized as fundamentally important to understanding the structure and function of genetic pathways and the evolutionary dynamics of complex genetic systems. With the advent of high-throughput functional genomics and the emergence of systems approaches to biology, as well as a new-found ability to pursue the genetic basis of evolution down to specific molecular changes, there is a renewed appreciation both for the importance of studying gene interactions and for addressing these questions in a unified, quantitative manner.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/ccab71dd27f5346f481c595bf84d39468e0176ad

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Citations in the corpus

A Tutorial on Interaction (2014, background): “…not if just one or the other is present, it should be noted, that even such " mechanistic interaction " , does not imply that the two exposures are physically interacting in any real sense (Siemiatycki and Thomas, 1981; Thompson, 1991; VanderWeele and Robins, 2007; Phillips, 2008; Cordell, 2009).”
Progress and Promise of Genome-Wide Association Studies for Human Complex Trait Genetics (2011, background): “Gene–gene or more specifically variant–variant interactions (epistasis) have been identified in model organisms (Phillips 2008; Tyler et al. 2009) and anecdotally in humans (Sing and Davignon 1985; Zerba et al. 2000; Small et al. 2002; Combarros et al. 2009), but to date have not been widely…”
Should evolutionary geneticists worry about higher-order epistasis? (2013, background): “The recognition of epistasis between pairs of mutations in both discrete, Mendelian [1] and continuous [2,3] traits goes back roughly 100 years, but recent experimental advances draw attention to interactions between more than two mutations.”
Epistasis and Adaptation on Fitness Landscapes (2022, background): “Many fitness landscape studies come from systems and molecular biology, where epistasis is considered a natural consequence of interactions within and between genes (reviewed in Domingo et al. 2019, Phillips 2008, Costanzo et al. 2019, Athavale et al. 2014).”
Inferring fitness landscapes by regression produces biased estimates of epistasis (2014, background): “The dynamics of an adapting population fundamentally depend on characteristics of the organism’s fitness landscape [6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24].”
Empirical fitness landscapes and the predictability of evolution (2014, neutral): “f(σ) = a(0) + ai((1))σi + aij((2))σiσj + aijk((3))σiσjσk + .”
Epistasis in protein evolution (2016, background): “from the effects of A and B alone, regardless of the direction of the effect.(1) (E and F) The two mutations exhibit positive”
GAMETES: a fast, direct algorithm for generating pure, strict, epistatic models with random architectures (2012, background): “…jason.h.moore@dartmouth.edu Department of Genetics, Institute for Quantitative Biomedical Sciences, Dartmouth Medical School, Lebanon, NH, USA Background: Geneticists who look beyond single locus disease associations require additional strategies for the detection of complex multi-locus effects.”
BOOST: A fast approach to detecting gene-gene interactions in genome-wide case-control studies (2010, background): “interactions than statistical epistasis.(2) Compositional epistasis has recently been shown to be empirically testable via a statistical approach.”
The genetics of quantitative traits: challenges and prospects (2009, background): “Epistatic interactions identify genetic networks that affect complex trait”