The genetic basis of complex traits and diseases –– because they represent multifactorial traits –– results from the combined action of many DNA-sequence variants, plus epigenetic effects, plus environmental factors. It continues to remain unclear whether these variants act individually in an additive manner, or via non-additive epistatic interactions. Epistasis (gene-gene interactions) has been widely observed in model organisms such as yeast, roundworm, fruit fly, and mouse. However, it has been more difficult to detect in humans, most likely due to diverse genetic backgrounds, low allele frequencies, limited sample sizes, complexity of interactions, insufficient effect-sizes, and methodological limitations]. Nonetheless, a number of genome-wide interaction-based association studies in humans have provided evidence for epistasis in various complex traits and diseases. Yet, concerns remain over whether observed epistatic interactions are due to statistical or experimental artifacts.
To understand better the contribution of epistasis to complex traits, authors [see attached] studied mouse Chromosome-Substitution Strains (CSSs) . For each CSS, a single chromosome in a host strain has been replaced by the corresponding chromosome from a donor strain; this provides an efficient model for mapping quantitative trait loci (QTLs) on a fixed genetic background. This approach is in contrast to populations having many segregating variants such as advanced intercross lines, heterogeneous stock lines, or typical analyses in human populations. Given the presumed importance of genetic background-effects in complex traits, authors hypothesized the fixed genetic backgrounds of CSSs can provide an innovative means for detecting large-scale genetic interactions.
In this study in mice, authors discovered that genetic regulation of blood sugar levels, and gene expression in liver, were predominantly controlled by non-additive interactions, whereas body weight was predominantly controlled by additive interactions. Importantly, the expression level of ~25% of all genes in liver was controlled by non-additive interactions. Non-additive interactions typically acted to return trait values to levels detected in control mice, thus contributing to a decrease in trait variation. Authors also demonstrated that –– not accounting for non-additive interactions –– significantly underestimates the phenotypic effect of a genetic variant on a particular genetic background; this finding suggests that many previously identified risk loci may have significantly larger effects on disease susceptibility in a subset of individuals. These studies highlight the importance of understanding additive vs non-additive epistatic interactions between genetic variants –– to understand more clearly disease risk and personalize clinical care.
PLoS Genet Sept 2o17; 13: e1007025