What factors explain and drive evolution? Neo-Darwinism holds that random mutations occur in the genome and natural selection serves as a sieve, favoring beneficial mutations and eliminating deleterious ones. The only alternative so far to the idea that mutation is essentially random has been Lamarckism, but this alternative is severely limited. A new theory published by the PI, called Interaction-based Evolution (IBE), argues that the fundamental nature of mutation is neither random nor Lamarckian. Instead, natural selection interacts with a vast array of mutational mechanisms, leading to emergent novelty in nature and increasing complexity. This theory raises a testable prediction: Mutational mechanisms respond cumulatively to long-term selection pressures, imparting non-randomness and directionality to the origination of mutations.
We propose to test this prediction empirically in the human genome using three mutations of much interest: one protects against malaria, and the other two protect against African sleeping sickness (both life-threatening diseases common in Africa and, in the case of malaria, elsewhere). While the former has served as a quintessential example of random mutation, indirect evidence suggests that it actually originated non-randomly in accord with IBE; less is known about the other two. To test our predictions, we will measure whether the emergence rates of these mutations (not their frequencies in the population) are significantly higher in populations that have been subject to intense pathogen pressure for many generations than in populations that have not, using a novel method developed for this purpose. Positive results could open up the conversation on the fundamental nature of mutation and evolution by showing clearly and concretely that mutation is non-random after all, yet in an unexpected (non-Lamarckian) way. Deliverables include high-impact scientific publications and dissemination of the work in the media.