Stochastic epigenetic variation as a driving force of development, evolutionary adaptation, and disease

Abstract

Neo-Darwinian evolutionary theory is based on exquisite selection of phenotypes caused by small genetic variations, which is the basis of quantitative trait contribution to phenotype and disease. Epigenetics is the study of nonsequence-based changes, such as DNA methylation, heritable during cell division. Previous attempts to incorporate epigenetics into evolutionary thinking have focused on Lamarckian inheritance, that is, environmentally directed epigenetic changes. Here, we propose a new non-Lamarckian theory for a role of epigenetics in evolution. We suggest that genetic variants that do not change the mean phenotype could change the variability of phenotype; and this could be mediated epigenetically. This inherited stochastic variation model would provide a mechanism to explain an epigenetic role of developmental biology in selectable phenotypic variation, as well as the largely unexplained heritable genetic variation underlying common complex disease. We provide two experimental results as proof of principle. The first result is direct evidence for stochastic epigenetic variation, identifying highly variably DNA-methylated regions in mouse and human liver and mouse brain, associated with development and morphogenesis. The second is a heritable genetic mechanism for variable methylation, namely the loss or gain of CpG dinucleotides over evolutionary time. Finally, we model genetically inherited stochastic variation in evolution, showing that it provides a powerful mechanism for evolutionary adaptation in changing environments that can be mediated epigenetically. These data suggest that genetically inherited propensity to phenotypic variability, even with no change in the mean phenotype, substantially increases fitness while increasing the disease susceptibility of a population with a changing environment.DNA methylation | epigenetics | evolution | stochastic variation

Neonatal DNA methylation profile in human twins is specified by a complex interplay between intrauterine environmental and genetic factors, subject to tissue-specific influence

“…An elegant example of this was reported by Feinberg and colleagues, who demonstrated that the genome-wide DNA methylation profile in the livers of newborn inbred mice raised in identical environments was hypervariable at certain loci, termed variably methylated regions (VMRs) (Feinberg and Irizarry 2011). VMRs were enriched in genes involved in development and morphogenesis both in mice and unrelated humans (Feinberg et al 2010), and such genes are also discordantly methylated within our twin pairs (Supplemental Tables S9, S10).…”

“…Such studies are improving our understanding of the processes involved in the regulation of epigenetic variation and are disentangling the relative contributions of epigenetics, environment, and genetic variation, together with stochastic factors, in complex traits (Bell and Saffery 2012). This information is critical to understanding processes of development and evolution (Feinberg and Irizarry 2011) and for future potential epigenetic-based interventions in complex disease.…”

Identification of schizophrenia-associated loci by combining DNA methylation and gene expression data from whole blood

“…6 It has been suggested that epigenetic variation might be partly responsible for the missing heritability 7,8 and be involved in phenotypic variation. [9][10][11] Recent evidence shows that SZ susceptibility loci are enriched for gene expression QTLs, 12 and a similar enrichment exists for QTLs affecting DNA methylation and expression in bipolar disorder. 13 Given these results, we hypothesized that intersecting disease-related gene expression data with disease-related methylation data might lead to identification of genetic susceptibility loci.…”

Epigenetics and human obesity

“…The presence of co-ordinate variation at CpGs within a localised region can provide more confidence that differences seen are real and methods looking at variable methylated regions, as opposed to single sites, are increasingly being used in analysis of methylation data to overcome the problems associated with strict multiple testing corrections 89 . It has been proposed that particular regions of the genome show high levels of variance in methylation levels and that this might provide potential for gene expression levels to stably respond to environmental conditions 90 . This adaptability would confer a significant fitness advantage and has probably been subject to strong selection during the longer time scales of evolution, i.e.…”