Abstract

Thought to be directly and uniquely dependent from genotypes, the ontogeny of individual phenotypes is much more complicated. Individual genetics, environmental exposures, and their interaction are the three main determinants of individual’s phenotype. This picture has been further complicated a decade ago when the Lamarckian theory of acquired inheritance has been rekindled with the discovery of epigenetic inheritance, according to which acquired phenotypes can be transmitted through fertilization and affect phenotypes across generations. The results of Genome-Wide Association Studies have also highlighted a big degree of missing heritability in genetics and have provided hints that not only acquired phenotypes, but also individual’s genotypes affect phenotypes intergenerationally through indirect genetic effects. Here, we review available examples of indirect genetic effects in mammals, what is known of the underlying molecular mechanisms and their potential impact for our understanding of missing heritability, phenotypic variation. and individual disease risk.

Highlights

  • Years of genetics have attributed uniquely to genes the ability to generate and transfer phenotypes across generations (Gayon 2016)

  • To account for this, scientists have proposed a risk scoring system known as polygenic risk score (PRS), which is calculated by weighted sum of risk alleles in an individual and the corresponding effect sizes obtained from Genome-Wide Association Studies (GWAS) statistics summary, which allows more accurate assessment for individual’s disease risk (Lewis and Vassos 2020)

  • The same group has shown that specific knockout of EZH2 in the maternal germline leads to intergenerational overgrowth (Prokopuk et al 2018) evident in heterozygous offspring of homozygous mothers compared to heterozygous offspring of heterozygous mothers. These findings provide evidence that: 1. indirect genetic effects exist in mammals; 2. they can be induced by parental perturbation of both canonical epigenetic modifiers (Smarca5, Dnmt1, Lsd1, Utx, Eed, Ezh2) and genes with previously unknown epigenetic function (Kit, Y-chromosome associated genes, Obrq2a, Apobec1, Dnd1, A1cf, Ago2), and 3. they generally persist across several generations

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Summary

Introduction

Years of genetics have attributed uniquely to genes (and genotypes) the ability to generate and transfer phenotypes across generations (Gayon 2016). Complex genetic interactions between genes and gene variants associated with the same trait contribute to the phenotype and might explain specific “missing heritability”. The PRS should consider complex genetic interactions, which affect individual’s phenotypes and might determine the genetic bases of variation in quantitative traits and individual’s risk to complex diseases (Fang et al 2019; Hill et al 2008; Sackton and Hartl 2016; Zuk et al 2012). Some studies in model organisms have biologically validated some epistatic signals detected via statistical and computational approaches (Costanzo et al 2016; Mackay 2014, 2015; Zuk et al 2012) and in humans, two recent studies have combined statistical and functional approaches to identify functional epistatic interactions in the pathogenesis and risk to coronary artery disease (CAD) (Li et al 2020) and Scleroderma (Tyler et al 2020)

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