The causes of epistasis

J.A.G.M. de Visser, T.F. Cooper, S.F. Elena

Research output: Contribution to journalArticleAcademicpeer-review

114 Citations (Scopus)

Abstract

Since Bateson’s discovery that genes can suppress the phenotypic effects of other genes, gene interactions— called epistasis—have been the topic of a vast research effort. Systems and developmental biologists study epistasis to understand the genotype–phenotype map, whereas evolutionary biologists recognize the fundamental importance of epistasis for evolution. Depending on its form, epistasis may lead to divergence and speciation, provide evolutionary benefits to sex and affect the robustness and evolvability of organisms. That epistasis can itself be shaped by evolution has only recently been realized. Here, we review the empirical pattern of epistasis, and some of the factors that may affect the form and extent of epistasis. Based on their divergent consequences, we distinguish between interactions with or without mean effect, and those affecting the magnitude of fitness effects or their sign. Empirical work has begun to quantify epistasis in multiple dimensions in the context of metabolic and fitness landscape models.We discuss possible proximate causes (such as protein function and metabolic networks) and ultimate factors (including mutation, recombination, and the importance of natural selection and genetic drift). We conclude that, in general, pleiotropy is an important prerequisite for epistasis, and that epistasis may evolve as an adaptive or intrinsic consequence of changes in genetic robustness and evolvability
Original languageEnglish
Pages (from-to)3617-3624
JournalProceedings of the Royal Society. B: Biological Sciences
Volume278
Issue number1725
DOIs
Publication statusPublished - 2011

Keywords

  • dna-bacteriophage phi-x174
  • deleterious mutations
  • antibiotic-resistance
  • sexual reproduction
  • escherichia-coli
  • saccharomyces-cerevisiae
  • compensatory mutations
  • synergistic epistasis
  • beneficial mutations
  • digital organisms

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