The completion of the Arabidopsis thaliana genome sequencing project represented the beginning of a new way to approach biological questions in plants (The Arabidopsis Genome Initiative, 2000). At a basic level, a fully sequenced genome makes it possible to predict the identity and structure of most genes. This information, in conjunction with recent advances in technology to quantitatively detect the expression of thousands of genes simultaneously, has greatly expanded the number of genes a biologist can study. Thus, the postgenome era is characterized by a wealth of data, but also by new challenges. Large data sets require analytical methods such as statistical analysis and computationally intensive methods, with which most biologists are not necessarily familiar. To address these challenges, the new biologist must collaborate with researchers from other fields such as computer science and engineering, to design experiments, interpret data, generate models and build bioinformatics infrastructure to share data. While large data sets facilitate rapid progress using traditional reductionist approaches to answering biological questions, they also enable a new approach termed systems biology that aims to understand the structure of large-scale phenomena not easily studied through the examination of individual genes. In this chapter, we will give an overview of the technologies that allow the root developmental biologist to acquire large data sets and examine how these techniques have been used to study root development. Finally, we will explore the types of questions that remain in root developmental biology for which genomic approaches are likely to provide useful insights.