Publicly available maize lines are a resource for studying quantitative genetic variation in plants. This dataset includes cluster or subpopulation information, phenotypic data, and single nucleotide polymorphism (SNP) data for 272 maize lines developed by the University of Minnesota, other universities, and seed companies. The lines were evaluated at multiple locations in Minnesota in 2011 and 2012 for different phenological, morphological, and kernel composition traits. The lines were genotyped for 56,110 SNP loci on the Maize SNP50 Beadchip (Illumina). Filtering for SNP data quality led to data for 28,626 SNP loci for the 272 maize lines. Population structure analysis showed that the maize lines clustered into five subpopulations (A321 or Minnesota 13, B73, Mo17, Oh43, and PH207 or Iodent) that represented most of the U.S. Corn Belt diversity (Schaefer and Bernardo 2013a, Crop Science 53:1529-1536). Genomewide association mapping revealed marker-trait associations for male flowering date, female flowering date, plant height, ear height, and kernel concentration for oil, protein, and starch (Schaefer and Bernardo 2013b, Crop Science 53:2518-2529). The covariance between relatives is a tenet in quantitative genetics, but such classical theory has ignored any resemblance between individuals unrelated by pedigree. Analysis of this maize dataset showed that a covariance between nonrelatives in maize is not ubiquitous but it is sometimes rpesent for specific traits and for certain groups of unrelated individuals (Bernardo 2022, Heredity).