Quantitative genetics and the missing heritability problem

For many heritable traits, including susceptibility to common diseases in humans, regions of the genome uncovered by genetic mapping studies explain only a minority of the heritable contribution to trait variance in the population. This “missing heritability problem” has become a central issue in human genetics, as well as in genetics of quantitative traits more broadly. We set out to investigate genetics of quantitative traits and the causes of missing heritability issues in yeast, a simple genetic model organism. To do so, we set up a very large panel of progeny from a cross between two divergent parent strains. We then used genomic approaches to accurately estimate different sources of heritable variation for 46 quantitative traits and to detect underlying genomic regions with high statistical power. We find that the detected regions explain nearly the entire additive contribution to heritable variation for the traits studied. We also quantify the contribution to heritability of nonlinear gene-gene interactions. Our results are consistent with the hypothesis that missing heritability arises primarily from a very large number of genetic factors with very small individual effects. These factors can be discovered in studies with sufficiently large sample sizes, although the optimal study designs depend on the population frequency spectra of the factors. I will describe ongoing work to measure the contributions of factors with different population frequencies.