Digging deeper: high-resolution genome-scale data yields new insights into root biology

Abstract

Development in multicellular organisms is the result of designated cellular programs occurring at specific points in time and space. The root is an excellent model to address how spatio-temporal complexity impacts organ development. High-resolution 'omic' approaches have delineated the transcriptional, proteomic, metabolomic, and small RNA profiles of multiple cell types in the Arabidopsis root. Similar approaches have shed light on root cell-type specific transcriptional programs in rice and soybean. These data are being used to identify specific spatio-temporal mechanisms of root development, dissect regulatory networks that control cell identity, and understand hormone responses in the root. Computational modeling of these data combined with new advances in imaging technologies is generating new biological insights into root growth and development.