  Modelling genetic phenomena affecting biological traits is important for the
development of agriculture as it allows breeders to predict the potential of
breeding for certain traits. One such phenomenon is heterosis or hybrid vigor:
crossing individuals from genetically distinct populations often results in
improvements in quantitative traits, such as growth rate, biomass production
and stress resistance. Heterosis has become a very useful tool in global
agriculture, but its genetic basis remains controversial and its effects hard
to predict. We have taken a computational approach to studying heterosis,
developing a simulation of evolution, independent reassortment of alleles and
hybridization of Gene Regulatory Networks (GRNs) in a Boolean framework.
Fitness is measured as the ability of a network to respond to external inputs
in a pre-defined way. Our model reproduced common experimental observations on
heterosis using only biologically justified parameters. Hybrid vigor was
observed and its extent was seen to increase as parental populations diverged,
up until a point of sudden collapse of hybrid fitness. We also reproduce, for
the first time in a model, the fact that hybrid vigor cannot easily be fixed by
within a breeding line, currently an important limitation of the use of hybrid
crops. The simulation allowed us to study the effects of three standard models
for the genetic basis of heterosis and the level of detail in our model allows
us to suggest possible warning signs of the impending collapse of hybrid vigor
in breeding. In addition, the simulation provides a framework that can be
extended to study other aspects of heterosis and alternative evolutionary
scenarios.
