To make a case for or against a trend in the evolution of complexity in biological evolution, complexity needs to be both rigorously defined and measurable. A recent information-theoretic (but intuitively evident) definition identifies genomic complexity with the amount of information a sequence stores about its environment. We investigate the evolution of genomic complexity in populations of digital organisms and monitor in detail the evolutionary transitions that increase complexity. We show that, because natural selection forces genomes to behave as a natural ''Maxwell Demon,'' within a fixed environment, genomic complexity is forced to increase.

Animal species adapt to changes in their environment, including man-made changes such as the introduction of insecticides, through selection for advantageous genes already present in populations or newly arisen through mutation. A possible alternative mechanism is the acquisition of adaptive genes from related species via a process known as adaptive introgression. Differing levels of insecticide resistance between two African malaria vectors, Anopheles coluzzii and Anopheles gambiae, have been attributed to assortative mating between the two species. In a previous study, we reported two bouts of hybridization observed in the town of Selinkenyi, Mali in 2002 and 2006. These hybridization events did not appear to be directly associated with insecticide-resistance genes. We demonstrate that during a brief breakdown in assortative mating in 2006, A. coluzzii inherited the entire A. gambiae-associated 2L divergence island, which includes a suite of insecticide-resistance alleles. In this case, introgression was coincident with the start of a major insecticide-treated bed net distribution campaign in Mali. This suggests that insecticide exposure altered the fitness landscape, favoring the survival of A. coluzzii/A. gambiae hybrids, and provided selection pressure that swept the 2L divergence island through A. coluzzii populations in Mali. We propose that the work described herein presents a unique description of the temporal dynamics of adaptive introgression in an animal species and represents a mechanism for the rapid evolution of insecticide resistance in this important vector of human malaria in Africa.

Digital organisms are computer programs that self-replicate, mutate and adapt by natural selection. They offer an opportunity to test generalizations about living systems that may extend beyond the organic life that biologists usually study. Here we have generated two classes of digital organism: simple programs selected solely for rapid replication, and complex programs selected to perform mathematical operations that accelerate replication through a set of defined 'metabolic' rewards. To examine the differences in their genetic architecture, we introduced millions of single and multiple mutations into each organism and measured the effects on the organism's fitness. The complex organisms are more robust than the simple ones with respect to the average effects of single mutations. Interactions among mutations are common and usually yield higher fitness than predicted from the component mutations assuming multiplicative effects; such interactions are especially important in the complex organisms. Frequent interactions among mutations have also been seen in bacteria, fungi and fruitflies. Our findings support the view that interactions are a general feature of genetic systems.