Deleterious mutations inevitably emerge in any evolutionary process and are 
speculated to decisively influence the structure of the genome. Meiosis, which 
is thought to play a major role in handling mutations on the population level, 
recombines chromosomes via non-randomly distributed hot spots for meiotic 
recombination. In many genomes, various types of genetic elements are 
distributed in patterns that are currently not well understood. In particular, 
important (essential) genes are arranged in clusters, which often cannot be 
explained by a functional relationship of the involved genes. Here we show by 
computer simulation that essential gene (EG) clustering provides a fitness 
benefit in handling deleterious mutations in sexual populations with variable 
levels of inbreeding and outbreeding. We find that recessive lethal mutations 
enforce a selective pressure towards clustered genome architectures. Our 
simulations correctly predict (i) the evolution of non-random distributions of 
meiotic crossovers, (ii) the genome-wide anti-correlation of meiotic crossovers 
and EG clustering, (iii) the evolution of EG enrichment in pericentromeric 
regions and (iv) the associated absence of meiotic crossovers (cold 
centromeres). Our results furthermore predict optimal crossover rates for yeast 
chromosomes, which match the experimentally determined rates. Using a 
Saccharomyces cerevisiae conditional mutator strain, we show that haploid lethal 
phenotypes result predominantly from mutation of single loci and generally do 
not impair mating, which leads to an accumulation of mutational load following 
meiosis and mating. We hypothesize that purging of deleterious mutations in 
essential genes constitutes an important factor driving meiotic crossover. 
Therefore, the increased robustness of populations to deleterious mutations, 
which arises from clustered genome architectures, may provide a significant 
selective force shaping crossover distribution. Our analysis reveals a new 
aspect of the evolution of genome architectures that complements insights about 
molecular constraints, such as the interference of pericentromeric crossovers 
with chromosome segregation.