Plant architecture, phenology and yield components of cultivated plants have repeatedly been shaped by selection to meet human needs and adaptation to different environments. Here we assessed the genetic architecture of 24 correlated maize traits that interact during plant cycle. Overall, 336 lines were phenotyped in a network of 9 trials and genotyped with 50K singlenucleotide polymorphisms. Phenology was the main factor of differentiation between genetic groups. Then yield components distinguished dents from lower yielding genetic groups. However, most of trait variation occurred within group and we observed similar overall and within group correlations, suggesting a major effect of pleiotropy and/or linkage. We found 34 quantitative trait loci (QTLs) for individual traits and six for trait combinations corresponding to PCA coordinates. Among them, only five were pleiotropic. We found a cluster of QTLs in a 5 Mb region around Tb1 associated with tiller number, ear row number and the first PCA axis, the latter being positively correlated to flowering time and negatively correlated to yield. Kn1 and ZmNIP1 were candidate genes for tillering, ZCN8 for leaf number and Rubisco Activase 1 for kernel weight. Experimental repeatabilities, numbers of QTLs and proportion of explained variation were higher for traits related to plant development such as tillering, leaf number and flowering time, than for traits affected by growth such as yield components. This suggests a simpler genetic determinism with larger individual QTL effects for the first category. Although technology to support this process has dramatically evolved, especially in recent decades, breeders' objectives have not fundamentally changed over the last 10 000 years. They still have to overcome the difficulty of conducting multiple trait selection in different and variable environments and their choices are often trade-offs between an ideal plant architecture, product quality, yield and adaptation to targeted environments. Low cost genotyping can accelerate the selection of large effect beneficial alleles and high throughput genotyping can improve the accuracy of breeding value predictions for multi-traits controlled by small effect quantitative trait loci (QTLs).In cereals, yield remains the main objective even though it may be negatively correlated with some quality traits. Yield is a complex trait to predict as it is the result of many trait interactions during plant development and growth. The objective is to combine plant architecture that maximizes light interception, phenology that synchronizes reproduction stage with optimal environmental conditions to minimize abortion, inflorescence architecture for optimal seed set, and numerous factors contributing to environmental adaptation and grain filling.