epistasis

Flint J & Mackay TFC 2009 Genetic architecture of quantitative traits in mice, flies, and humans. Genome Res 19:723-733.

• to map QTLs in rodents, about 100 markers and a few hundred animals were sufficient to provide robust statistical evidence for the location of genetic variants contributing to quantitative phenotypic variation
• mapping QTLs was also relatively easy in flies (and much cheaper than in rodents)
• the picture that emerged from both organisms was broadly similar
• mMost of the early mapping studies revealed that a few QTLs with relatively large effects accounted for the bulk of phenotypic variation in most traits
• the estimates of effect size from model organisms suggested that QTLs explaining as much as 10% of the phenotypic variance might be found, in which case linkage studies using a few hundred families would be sufficient to detect them
• subsequent studies in mice and flies using larger samples began to reveal a more complex picture
• doubling the number of mice in the mapping population from 800 to 1600 more than doubled the number of QTLs found to influence a measure of fear-related behavior

• high-resolution mapping of QTLs revealed more complex genetic architectures than implicated from the initial genome scans
• single QTLs identified in genome scans typically fractionated into multiple, closely linked QTLs, often with opposite effects

• although more QTLs were discovered, the results were still inconsistent with the "infinitesimal" model of quantitative genetic variation

• the small effect sizes reported in human studies do not necessarily mean that the infinitesimal model is a useful description of quantitative genetic variation in human populations
• the loci discovered account for remarkably small amounts of the total phenotypic variance
• for height, all known loci explain <5% of the variance
• for a measure of obesity (body mass index) known loci account for <1% of the variance

• epistatic interactions (defined as a statistical interaction between genotypes at two [or more] loci) are difficult to detect in QTL mapping studies
• the large number of pairwise tests for marker–marker interactions imposes a low experiment-wise significance threshold

• a Bayesian method, developed to deal with the problem of testing multiple interactions, estimates epistatic effects by generating posterior samples from the joint posterior distribution of all unknowns, including the main and epistatic effects, given the observed data
• Yi and colleagues detected several epistatic QTL that were not found by frequentist methods
• this should not lead to the conclusion that epistasis is universal
• despite an extensive search, little evidence for epistasis emerges, as, for example, in the case of fear-related behavior in mice

• there are two senses in which one can discuss epistatic effects:
• in reference to the contribution of epistasis to the mean differences between genotypes ("physiological" epistasis)
• in reference to the contribution of epistatic interactions to the population genetic variance ("statistical" epistasis)
• all of the model organism studies measured the contribution of epistasis in the former sense
• epistatic variance, like other components of genetic variance, depends on both effects and allele frequencies
• large effects on the mean difference between genotypes may not translate to large effects on the variance