The generally stronger effects of protein-coding mutations leads to a sampling bias, in that more severe phenotypes are not only more easily discerned but have also been more likely to attract further study, both in medical contexts and in model organisms. In medicine, mutations involving catastrophic component damage have been traditionally referred to as “monogenic diseases” and were the primary targets of study in the pioneering days of human genomics, just a decade or two ago, when the protein-coding genes underpinning cystic fibrosis, Huntington disease, and Duchenne muscular dystrophy, among others, were identified by positional mapping and cloning approaches. Thus, in humans, mutation mapping is still both a young science and extraordinarily difficult due to the sheer complexity of the genome, which naturally led to an initial focus on severe loss-of-function diseases that exhibit simple inheritance patterns with high penetrance (“single gene–large effect”) making them amenable to identification. This is now changing with the increasing availability of human genome sequences, and the application of genome-wide association (GWA) studies to the mapping of the genetic components of complex traits, wherein lies the majority of the health burden and the majority of the interesting phenotypic differences between individuals and species.
