4.5 Review

Quantitative epigenetics and evolution

Journal

HEREDITY
Volume 121, Issue 3, Pages 210-224

Publisher

SPRINGERNATURE
DOI: 10.1038/s41437-018-0114-x

Keywords

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Funding

  1. Society for the Study of Evolution
  2. Sociedade Brasileira de Genetica
  3. National Science Foundation (USA) through a Research Opportunity Award (ROA) [DEB-1419960, IOS-1556820]
  4. Direct For Biological Sciences
  5. Division Of Integrative Organismal Systems [1556738] Funding Source: National Science Foundation

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Epigenetics refers to chemical modifications of chromatin or transcribed DNA that can influence gene activity and expression without changes in DNA sequence. The last 20 years have yielded breakthroughs in our understanding of epigenetic processes that impact many fields of biology. In this review, we discuss how epigenetics relates to quantitative genetics and evolution. We argue that epigenetics is important for quantitative genetics because: (1) quantitative genetics is increasingly being combined with genomics, and therefore we should expand our thinking to include cellular-level mechanisms that can account for phenotypic variance and heritability besides just those that are hard-coded in the DNA sequence; and (2) epigenetic mechanisms change how phenotypic variance is partitioned, and can thereby change the heritability of traits and how those traits are inherited. To explicate these points, we show that epigenetics can influence all aspects of the phenotypic variance formula: V-P (total phenotypic variance) = V-G (genetic variance) + V-E (environmental variance) + V-GxE (genotype-by-environment interaction) + 2COV(GE) (the genotype-environment covariance) + V-epsilon (residual variance), requiring new strategies to account for different potential sources of epigenetic effects on phenotypic variance. We also demonstrate how each of the components of phenotypic variance not only can be influenced by epigenetics, but can also have evolutionary consequences. We argue that no sources of epigenetic effects on phenotypic variance can be easily cast aside in a quantitative genetic research program that seeks to understand evolutionary processes.

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