Pine cones that remain closed and retain seeds until fire causes the cones to open (cone serotiny) represent a key adaptive trait in a variety of pine species. In lodgepole pine, there is substantial geographical variation in serotiny across the Rocky Mountain region. This variation in serotiny has evolved as a result of geographically divergent selection, with consequences that extend to forest communities and ecosystems. An understanding of the genetic architecture of this trait is of interest owing to the wide-reaching ecological consequences of serotiny and also because of the repeated evolution of the trait across the genus. Here, we present and utilize an inexpensive and time-effective method for generating population genomic data. The method uses restriction enzymes and PCR amplification to generate a library of fragments that can be sequenced with a high level of multiplexing. We obtained data for more than 95 000 single nucleotide polymorphisms across 98 serotinous and nonserotinous lodgepole pines from three populations. We used a Bayesian generalized linear model (GLM) to test for an association between genotypic variation at these loci and serotiny. The probability of serotiny varied by genotype at 11 loci, and the association between genotype and serotiny at these loci was consistent in each of the three populations of pines. Genetic variation across these 11 loci explained 50% of the phenotypic variation in serotiny. Our results provide a first genome-wide association map of serotiny in pines and demonstrate an inexpensive and efficient method for generating population genomic data.