Single drawback have Nucleotide different (e.g. properties ascertainment Polymorphism (e.g. bias), calling (SNP) which rate, array lead minor and us to allele re-sequencing study frequency the complementarity technologies profile) and and consequences of using them separately or combined in diversity analyses and Genome-Wide Association Studies (GWAS). We performed GWAS on three traits (grain yield, plant height and male flowering time) measured in 22 environments on a panel of 247 diverse dent maize inbred lines using three genotyping technologies (Genotyping-By-Sequencing, Illumina Infinium 50K and Affymetrix Axiom 600K arrays). The effects of ascertainment bias of both arrays were negligible for deciphering global genetic trends of diversity in this panel and for estimating relatedness. We developed an original approach based on linkage disequilibrium (LD) extent in order to determine whether SNPs significantly associated with a trait and that are physically linked should be considered as a single QTL or several independent QTLs. Using this approach, we showed that the combination of the three technologies, which have different SNP distribution and density, allowed us to detect more Quantitative Trait Loci (QTLs, gain in power) and potentially refine the localization of the causal polymorphisms (gain in position). Conceptually different technologies are complementary for detecting QTLs by tagging different haplotypes in association studies. Considering LD, marker density and the combination of different technologies (arrays and re-sequencing), the genotypic data presently available were most likely enough to well represent polymorphisms in the centromeric regions, whereas using more markers would be beneficial for telomeric regions.