Correct daily phasing of transcription confers an adaptive advantage to almost all organisms, including higher plants. In this study, we describe a hypothesis-driven network discovery pipeline that identifies biologically relevant patterns in genome-scale data. To demonstrate its utility, we analyzed a comprehensive matrix of time courses interrogating the nuclear transcriptome of Arabidopsis thaliana plants grown under different thermocycles, photocycles, and circadian conditions. We show that 89% of Arabidopsis transcripts cycle in at least one condition and that most genes have peak expression at a particular time of day, which shifts depending on the environment. Thermocycles alone can drive at least half of all transcripts critical for synchronizing internal processes such as cell cycle and protein synthesis. We identified at least three distinct transcription modules controlling phase-specific expression, including a new midnight specific module, PBX/TBX/SBX. We validated the network discovery pipeline, as well as the midnight specific module, by demonstrating that the PBX element was sufficient to drive diurnal and circadian condition-dependent expression. Moreover, we show that the three transcription modules are conserved across Arabidopsis, poplar, and rice. These results confirm the complex interplay between thermocycles, photocycles, and the circadian clock on the daily transcription program, and provide a comprehensive view of the conserved genomic targets for a transcriptional network key to successful adaptation.

RankProd is available at Bioconductor http://www.bioconductor.org. A web-based interface will soon be available at http://cactus.salk.edu/RankProd

The DIURNAL project (http://diurnal.cgrb.oregonstate.edu/) provides a graphical interface for mining and viewing diurnal and circadian microarray data for Arabidopsis thaliana, poplar, and rice. The database is searchable and provides access to several user-friendly Web-based data-mining tools with easy-to-understand output. The associated tools include HAYSTACK

Spirodela polyrhiza is a fast-growing aquatic monocot with highly reduced morphology, genome size and number of protein-coding genes. Considering these biological features of Spirodela and its basal position in the monocot lineage, understanding its genome architecture could shed light on plant adaptation and genome evolution. Like many draft genomes, however, the 158-Mb Spirodela genome sequence has not been resolved to chromosomes, and important genome characteristics have not been defined. Here we deployed rapid genome-wide physical maps combined with high-coverage short-read sequencing to resolve the 20 chromosomes of Spirodela and to empirically delineate its genome features. Our data revealed a dramatic reduction in the number of the rDNA repeat units in Spirodela to fewer than 100, which is even fewer than that reported for yeast. Consistent with its unique phylogenetic position, small RNA sequencing revealed 29 Spirodela-specific microRNA, with only two being shared with Elaeis guineensis (oil palm) and Musa balbisiana (banana). Combining DNA methylation data and small RNA sequencing enabled the accurate prediction of 20.5% long terminal repeats (LTRs) that doubled the previous estimate, and revealed a high Solo:Intact LTR ratio of 8.2. Interestingly, we found that Spirodela has the lowest global DNA methylation levels (9%) of any plant species tested. Taken together our results reveal a genome that has undergone reduction, likely through eliminating non-essential protein coding genes, rDNA and LTRs. In addition to delineating the genome features of this unique plant, the methodologies described and large-scale genome resources from this work will enable future evolutionary and functional studies of this basal monocot family.