%0 Journal Article %J Plant Cell %D 2014 %T Paired-end analysis of transcription start sites in Arabidopsis reveals plant-specific promoter signatures. %A Morton, Taj %A Petricka, Jalean %A Corcoran, David L %A Li, Song %A Winter, Cara M %A Carda, Alexa %A Benfey, Philip N %A Ohler, Uwe %A Megraw, Molly %K Arabidopsis %K Arabidopsis Proteins %K Binding Sites %K Cluster Analysis %K DNA, Plant %K Gene Expression Regulation, Plant %K Genome, Plant %K Models, Genetic %K Nucleotide Motifs %K Plant Roots %K Promoter Regions, Genetic %K RNA, Messenger %K RNA, Plant %K Sequence Analysis, DNA %K Species Specificity %K TATA Box %K Transcription Factors %K Transcription Initiation Site %X

Understanding plant gene promoter architecture has long been a challenge due to the lack of relevant large-scale data sets and analysis methods. Here, we present a publicly available, large-scale transcription start site (TSS) data set in plants using a high-resolution method for analysis of 5' ends of mRNA transcripts. Our data set is produced using the paired-end analysis of transcription start sites (PEAT) protocol, providing millions of TSS locations from wild-type Columbia-0 Arabidopsis thaliana whole root samples. Using this data set, we grouped TSS reads into "TSS tag clusters" and categorized clusters into three spatial initiation patterns: narrow peak, broad with peak, and weak peak. We then designed a machine learning model that predicts the presence of TSS tag clusters with outstanding sensitivity and specificity for all three initiation patterns. We used this model to analyze the transcription factor binding site content of promoters exhibiting these initiation patterns. In contrast to the canonical notions of TATA-containing and more broad "TATA-less" promoters, the model shows that, in plants, the vast majority of transcription start sites are TATA free and are defined by a large compendium of known DNA sequence binding elements. We present results on the usage of these elements and provide our Plant PEAT Peaks (3PEAT) model that predicts the presence of TSSs directly from sequence.

[Link to Additional Data and Supplementary Materials]

%B Plant Cell %V 26 %P 2746-60 %8 2014 Jul %G eng %N 7 %R 10.1105/tpc.114.125617 %0 Journal Article %J Proc Natl Acad Sci U S A %D 2012 %T The protein expression landscape of the Arabidopsis root. %A Petricka, Jalean J %A Schauer, Monica A %A Megraw, Molly %A Breakfield, Natalie W %A Thompson, J Will %A Georgiev, Stoyan %A Soderblom, Erik J %A Ohler, Uwe %A Moseley, Martin Arthur %A Grossniklaus, Ueli %A Benfey, Philip N %K Arabidopsis %K Arabidopsis Proteins %K Base Sequence %K Chromatography, Liquid %K DNA Primers %K Gene Expression Profiling %K Plant Roots %K Plants, Genetically Modified %K Protein Array Analysis %K Protein Interaction Mapping %K Proteome %K Proteomics %K RNA, Plant %K Tandem Mass Spectrometry %X

Because proteins are the major functional components of cells, knowledge of their cellular localization is crucial to gaining an understanding of the biology of multicellular organisms. We have generated a protein expression map of the Arabidopsis root providing the identity and cell type-specific localization of nearly 2,000 proteins. Grouping proteins into functional categories revealed unique cellular functions and identified cell type-specific biomarkers. Cellular colocalization provided support for numerous protein-protein interactions. With a binary comparison, we found that RNA and protein expression profiles are weakly correlated. We then performed peak integration at cell type-specific resolution and found an improved correlation with transcriptome data using continuous values. We performed GeLC-MS/MS (in-gel tryptic digestion followed by liquid chromatography-tandem mass spectrometry) proteomic experiments on mutants with ectopic and no root hairs, providing complementary proteomic data. Finally, among our root hair-specific proteins we identified two unique regulators of root hair development.

%B Proc Natl Acad Sci U S A %V 109 %P 6811-8 %8 2012 May 1 %G eng %N 18 %R 10.1073/pnas.1202546109 %0 Journal Article %J Mol Syst Biol %D 2011 %T A stele-enriched gene regulatory network in the Arabidopsis root. %A Brady, Siobhan M %A Zhang, Lifang %A Megraw, Molly %A Martinez, Natalia J %A Jiang, Eric %A Yi, Charles S %A Liu, Weilin %A Zeng, Anna %A Taylor-Teeples, Mallorie %A Kim, Dahae %A Ahnert, Sebastian %A Ohler, Uwe %A Ware, Doreen %A Walhout, Albertha J M %A Benfey, Philip N %K Arabidopsis %K Arabidopsis Proteins %K Gene Expression Profiling %K Gene Regulatory Networks %K MicroRNAs %K Plant Roots %K Reproducibility of Results %K Systems Biology %K Transcription Factors %K Two-Hybrid System Techniques %X

Tightly controlled gene expression is a hallmark of multicellular development and is accomplished by transcription factors (TFs) and microRNAs (miRNAs). Although many studies have focused on identifying downstream targets of these molecules, less is known about the factors that regulate their differential expression. We used data from high spatial resolution gene expression experiments and yeast one-hybrid (Y1H) and two-hybrid (Y2H) assays to delineate a subset of interactions occurring within a gene regulatory network (GRN) that determines tissue-specific TF and miRNA expression in plants. We find that upstream TFs are expressed in more diverse cell types than their targets and that promoters that are bound by a relatively large number of TFs correspond to key developmental regulators. The regulatory consequence of many TFs for their target was experimentally determined using genetic analysis. Remarkably, molecular phenotypes were identified for 65% of the TFs, but morphological phenotypes were associated with only 16%. This indicates that the GRN is robust, and that gene expression changes may be canalized or buffered.

%B Mol Syst Biol %V 7 %P 459 %8 2011 Jan 18 %G eng %R 10.1038/msb.2010.114