RT Journal Article SR Electronic T1 A Large Scale Joint Analysis of Flowering Time Reveals Independent Temperate Adaptations in Maize JF bioRxiv FD Cold Spring Harbor Laboratory SP 086082 DO 10.1101/086082 A1 Kelly Swarts A1 Eva Bauer A1 Jeffrey C. Glaubitz A1 Tiffany Ho A1 Lynn Johnson A1 Yongxiang Li A1 Yu Li A1 Zachary Miller A1 Cinta Romay A1 Chris-Carolin Schöen A1 Tianyu Wang A1 Zhiwu Zhang A1 Edward S. Buckler A1 Peter Bradbury YR 2016 UL http://biorxiv.org/content/early/2016/11/07/086082.abstract AB Modulating days to flowering is a key mechanism in plants for adapting to new environments, and variation in days to flowering drives population structure by limiting mating. To elucidate the genetic architecture of flowering across maize, a quantitative trait, we mapped flowering in five global populations, a diversity panel (Ames) and four half-sib mapping designs, Chinese (CNNAM), US (USNAM), and European Dent (EUNAM-Dent) and Flint (EUNAM-Flint). Using whole-genome projected SNPs, we tested for joint association using GWAS, resampling GWAS and two regional approaches; Regional Heritability Mapping (RHM) (1, 2) and a novel method, Boosted Regional Heritability Mapping (BRHM). Direct overlap in significant regions detected between populations and flowering candidate genes was limited, but whole-genome cross-population predictive abilities were ≤0.78. Poor predictive ability correlated with increased population differentiation (r = 0.41), unless the parents were broadly sampled from across the North American temperate-tropical germplasm gradient; uncorrected GWAS results from populations with broadly sampled parents were well predicted by temperate-tropical FSTs in machine learning. Machine learning between GWAS results also suggested shared architecture between the American panels and, more distantly, the European panels, but not the Chinese panel. Machine learning approaches can reconcile non-linear relationships, but the combined predictive ability of all of the populations did not significantly enhance prediction of physiological candidates. While the North American-European temperate adaption is well studied, this study suggest independent temperate adaptation evolved in the Chinese panel, most likely in China after 1500, a finding supported by differential gene ontology term enrichment between populations.