E-GEOD-8934 - Transcription profiling of Arabidopsis 8 GFP marked lines with 2-3 replicates were used to augment existing microarray expression profiles of the root
Submitted on 31 August 2007, released on 16 June 2008, last updated on 2 May 2014
Transcriptional programs that regulate development are exquisitely controlled in space and time. Elucidating these programs that underlie development is essential to understanding the acquisition of cell and tissue identity. We present microarray expression profiles of a high resolution set of developmental time points within a single Arabidopsis root, and a comprehensive map of nearly all root cell-types. These cell-type specific transcriptional signatures often predict novel cellular functions. A computational pipeline identified dominant expression patterns that demonstrate transcriptional connections between disparate cell types. Dominant expression patterns along the root’s longitudinal axis do not strictly correlate with previously defined developmental zones, and in many cases, expression fluctuation along this axis was observed. Both robust co-regulation of gene expression and potential phasing of gene expression were identified between individual roots. Methods that combine these two sets of profiles demonstrate transcriptionally rich and complex programs that define Arabidopsis root development in both space and time. We used microarrays to profile expression of nearly all cell types in the Arabidopsis root, and to profile at high resolution, developmental time points along the root's longitudinal axis. Experiment Overall Design: Microarray expression profiles of 8 new GFP marked lines with 2-3 replicates were used to augment existing microarray expression profiles of the root. RNA isolated from 13 cross sections along a single root's longitudinal axis were also profiled by microarray analysis. An independent root with 12 sections were used as a biological replicate.
transcription profiling by array, unknown experiment type
A high-resolution root spatiotemporal map reveals dominant expression patterns. Siobhan M Brady, David A Orlando, Ji-Young Lee, Jean Y Wang, Jeremy Koch, José R Dinneny, Daniel Mace, Uwe Ohler, Philip N Benfey. Science 318(5851):801-6 (2007)