In order to safeguard feeding the growing human population, it is important to understand and exploit the genetic basis of quantitative traits. Next-generation sequencing technology has shown an effective performance advantage in genetic mapping and genome analysis of diverse genetic resources. In this study, we generated an ultra-high-density map which contains 1,151,856 of high quality SNPs between Mo17 and B73 and further verified in maize intermated B73 and Mo17 (IBM) Syn10 population to well complement the existing database. Moreover, combined with IBM Syn4 RIL population, we detected 135 QTLs for flowering time and plant height traits across two populations. Eighteen functional known genes and twenty-five candidate genes for flowering time and plant height trait were fine mapped into 2.21-4.96 Mb interval. Map expansion and segregation distortion were also analyzed, and evidence for inadvertent selection of early flowering time in the process of mapping population development were observed. Furthermore, an updated integrated map with 1,151,856 high quality SNPs, 2,916 traditional markers and 6,618 bin markers was constructed. The data was deposited into the iPlant Discovery Environment (DE) which provides a fundamental source of genetic data for maize genetic community in future.