TY - JOUR T1 - PlantSimLab-a modeling and simulation web tool for plant biologists JF - BMC Bioinformatics Y1 - 2019 A1 - S Ha A1 - E Dimitrova A1 - Stefan Hoops A1 - D Altarawy A1 - M Ansariola A1 - D Deb A1 - J Glazebrook A1 - R Hillmer A1 - H Shahin A1 - F Katagiri A1 - J McDowell A1 - M Megraw A1 - J Setubal A1 - BM Tyler A1 - Reinhard Laubenbacher VL - 20 UR - https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-3094-9 IS - 1 ER - TY - JOUR T1 - Paired-end analysis of transcription start sites in Arabidopsis reveals plant-specific promoter signatures. JF - Plant Cell Y1 - 2014 A1 - Morton, Taj A1 - Petricka, Jalean A1 - Corcoran, David L A1 - Li, Song A1 - Winter, Cara M A1 - Carda, Alexa A1 - Benfey, Philip N A1 - Ohler, Uwe A1 - Megraw, Molly KW - Arabidopsis KW - Arabidopsis Proteins KW - Binding Sites KW - Cluster Analysis KW - DNA, Plant KW - Gene Expression Regulation, Plant KW - Genome, Plant KW - Models, Genetic KW - Nucleotide Motifs KW - Plant Roots KW - Promoter Regions, Genetic KW - RNA, Messenger KW - RNA, Plant KW - Sequence Analysis, DNA KW - Species Specificity KW - TATA Box KW - Transcription Factors KW - Transcription Initiation Site AB -

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]

VL - 26 IS - 7 ER - TY - JOUR T1 - The protein expression landscape of the Arabidopsis root. JF - Proc Natl Acad Sci U S A Y1 - 2012 A1 - Petricka, Jalean J A1 - Schauer, Monica A A1 - Megraw, Molly A1 - Breakfield, Natalie W A1 - Thompson, J Will A1 - Georgiev, Stoyan A1 - Soderblom, Erik J A1 - Ohler, Uwe A1 - Moseley, Martin Arthur A1 - Grossniklaus, Ueli A1 - Benfey, Philip N KW - Arabidopsis KW - Arabidopsis Proteins KW - Base Sequence KW - Chromatography, Liquid KW - DNA Primers KW - Gene Expression Profiling KW - Plant Roots KW - Plants, Genetically Modified KW - Protein Array Analysis KW - Protein Interaction Mapping KW - Proteome KW - Proteomics KW - RNA, Plant KW - Tandem Mass Spectrometry AB -

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.

VL - 109 IS - 18 ER -