Multiparent or synthetic recombinant populations those created by combining distinct isogenic founders to establish a single recombinant background have emerged as a useful tool for dissecting the genetics of complex traits. Synthetic recombinant populations can be used to derive inbred lines in which quantitative traits can be mapped, or the recombinant populations themselves can be sampled for experimental evolution. Especially for the latter application, investigators generally value maximizing genetic variation in a recombinant population; in other words, a population harboring relatively equal contributions of the genetic backgrounds of each isogenic founder strain is a desirable resource. It is well-documented that in evolution experiments initiated from recombinant or outbred ancestral populations, the subsequent adaptation that occurs in evolved populations is driven by standing genetic variation, rather than de novo mutations. Despite the demonstrated importance of initial genetic variation to the adaptive process, little has been done to systematically evaluate methods of constructing a synthetic recombinant population, for creating resources for evolution experiments. Here we seek to address this issue by comparing patterns of genetic variation in different synthetic recombinant populations of Saccharomyces cerevisiae created using one of two combination strategies: pairwise crossing of isogenic strains or simple mixing of strains in equal proportion. We also explore the impact of the varying the number of parental strains used in each strategy. We find that more genetic variation is initially present and subsequently maintained over generations when population construction includes a round of pairwise crossing. We also observe that when using a given crossing strategy, increasing the number of parental strains typically increases genetic diversity. In summary, we suggest that when creating recombinant populations for use in experimental evolution studies, simply mixing founder strains in equal proportion may limit the adaptive potential of that population.