ORCID IDs: 0000-0002-9014-9516 (D.V.); 0000-0001-8918-0711 (J.J.B.K.).Quantitative traits in plants are controlled by a large number of genes and their interaction with the environment. To disentangle the genetic architecture of such traits, natural variation within species can be explored by studying genotype-phenotype relationships. Genome-wide association studies that link phenotypes to thousands of single nucleotide polymorphism markers are nowadays common practice for such analyses. In many cases, however, the identified individual loci cannot fully explain the heritability estimates, suggesting missing heritability. We analyzed 349 Arabidopsis accessions and found extensive variation and high heritabilities for different morphological traits. The number of significant genome-wide associations was, however, very low. The application of genomic prediction models that take into account the effects of all individual loci may greatly enhance the elucidation of the genetic architecture of quantitative traits in plants. Here, genomic prediction models revealed different genetic architectures for the morphological traits. Integrating genomic prediction and association mapping enabled the assignment of many plausible candidate genes explaining the observed variation. These genes were analyzed for functional and sequence diversity, and good indications that natural allelic variation in many of these genes contributes to phenotypic variation were obtained. For ACS11, an ethylene biosynthesis gene, haplotype differences explaining variation in the ratio of petiole and leaf length could be identified.The natural phenomena of mutation and recombination that change the genetic code with each generation have given rise to the enormous genetic diversity between and within species. Through evolutionary processes, such as drift, migration, and selection, plants have accumulated a vast number of molecular polymorphisms that enabled adaptation to a wide range of environments (Kooke and Keurentjes, 2012). With the recent advancements in genetic and genomic tools, this nucleotide diversity can be fully surveyed to identify causal polymorphisms for many different plant phenotypes. This should allow the identification of molecular changes that provided evolutionary advantages and beneficial characteristics in agronomically important traits.Through selection on variation in performance, plants have adapted to different environments. Plant performance is directly determined by life history traits, such as flowering time and growth rate, which in turn depend on genetics, morphology, physiology, and the environment (Roff, 2007;Kooke et al., 2015). Understanding the regulation of plant growth and morphology is therefore essential for the comprehension of plant performance. Arabidopsis has adapted to a wide range of environments and displays an extensive variety in morphological and growth-related phenotypes. Its small genome size, the publicly available