02741nas a2200145 4500008004100000245014300041210006900184260001200253490000600265520220300271100002402474700002202498700001802520856005702538 2020 eng d00aMetabolomics analysis reveals both plant variety and choice of hormone treatment modulate vinca alkaloid production in Catharanthus roseus0 aMetabolomics analysis reveals both plant variety and choice of h c09/20200 v43 a

The medicinal plant Catharanthus roseus produces numerous secondary metabolites of interest for the treatment of many diseases – most notably for the terpene indole alkaloid (TIA) vinblastine, which is used in the treatment of leukemia and Hodgkin's lymphoma. Historically, methyl jasmonate (MeJA) has been used to induce TIA production, but in the past, this has only been investigated in whole seedlings, cell culture, or hairy root culture. This study examines the effects of the phytohormones MeJA and ethylene on the induction of TIA biosynthesis and accumulation in the shoots and roots of 8‐day‐old seedlings of two varieties of C. roseus. Using LCMS and RT‐qPCR, we demonstrate the importance of variety selection, as we observe markedly different induction patterns of important TIA precursor compounds. Additionally, both phytohormone choice and concentration have significant effects on TIA biosynthesis. Finally, our study suggests that several early‐induction pathway steps as well as pathway‐specific genes are likely to be transcriptionally regulated. Our findings highlight the need for a complete set of'omics resources in commonly used C. roseus varieties and the need for caution when extrapolating results from one cultivar to another.

1 aFraser, Valerie, N.1 aPhilmus, Benjamin1 aMegraw, Molly uhttps://onlinelibrary.wiley.com/doi/10.1002/pld3.26701085nas a2200373 4500008004100000245010300041210006900144260001200213490000600225100002100231700002100252700001900273700001700292700001800309700002200327700001900349700001600368700002200384700002000406700002100426700001600447700001700463700001500480700002000495700002000515700001300535700001400548700001800562700001700580700001600597700001900613700001700632856006200649 2019 eng d00aArabidopsis bioinformatics resources: The current state, challenges, and priorities for the future0 aArabidopsis bioinformatics resources The current state challenge c01/20190 v31 aDoherty, Colleen1 aFriesner, Joanna1 aGregory, Brian1 aLoraine, Ann1 aMegraw, Molly1 aProvart, Nicholas1 aSlotkin, Keith1 aTown, Chris1 aAssmann, Sarah, M1 aAxtell, Michael1 aBerardini, Tanya1 aChen, Sixue1 aGehan, Malia1 aHuala, Eva1 aJaiswal, Pankaj1 aLarson, Stephen1 aLi, Song1 aMay, Sean1 aMichael, Todd1 aPires, Chris1 aTopp, Chris1 aWalley, Justin1 aWurtele, Eve uhttps://onlinelibrary.wiley.com/doi/full/10.1002/pld3.10902932nas a2200589 4500008004100000245010500041210006900146260001200215300001400227490000800241520124200249100002101491700002301512700001701535700002501552700001601577700002001593700001701613700002301630700002001653700001701673700002201690700002501712700002401737700002501761700002101786700002201807700002101829700002301850700001601873700001901889700001601908700002401924700001801948700002201966700002401988700002602012700001402038700001702052700002402069700002002093700002002113700001902133700001602152700002002168700002202188700001702210700002002227700002102247700002302268856005102291 2017 eng d00aThe Next Generation of Training for Arabidopsis Researchers: Bioinformatics and Quantitative Biology0 aNext Generation of Training for Arabidopsis Researchers Bioinfor c12/2017 a1499-15090 v1753 a
It has been more than 50 years since Arabidopsis (Arabidopsis thaliana) was first introduced as a model organism to understand basic processes in plant biology. A well-organized scientific community has used this small reference plant species to make numerous fundamental plant biology discoveries (Provart et al., 2016). Due to an extremely well-annotated genome and advances in high-throughput sequencing, our understanding of this organism and other plant species has become even more intricate and complex. Computational resources, including CyVerse,3 Araport,4 The Arabidopsis Information Resource (TAIR),5 and BAR,6 have further facilitated novel findings with just the click of a mouse. As we move toward understanding biological systems, Arabidopsis researchers will need to use more quantitative and computational approaches to extract novel biological findings from these data. Here, we discuss guidelines, skill sets, and core competencies that should be considered when developing curricula or training undergraduate or graduate students, postdoctoral researchers, and faculty. A selected case study provides more specificity as to the concrete issues plant biologists face and how best to address such challenges.
1 aFriesner, Joanna1 aAssmann, Sarah, M.1 aBastow, Ruth1 aBailey-Serres, Julia1 aBeynon, Jim1 aBrendel, Volker1 aBuell, Robin1 aBucksch, Alexander1 aBusch, Wolfgang1 aDemura, Taku1 aDinneny, Jose, R.1 aDoherty, Colleen, J.1 aEveland, Andrea, L.1 aFalter-Braun, Pascal1 aGehan, Malia, A.1 aGonzales, Michael1 aGrotewold, Erich1 aGutierrez, Rodrigo1 aKramer, Ute1 aKrouk, Gabriel1 aMa, Shisong1 aMarkelz, R.J., Cody1 aMegraw, Molly1 aMeyers, Blake, C.1 aMurray, James, A.H.1 aProvart, Nicholas, J.1 aRhee, Sue1 aSmith, Roger1 aSpalding, Edgar, P.1 aTaylor, Crispin1 aTeal, Tracy, K.1 aTor, Keiko, U.1 aTown, Chris1 aVaughn, Matthew1 aVierstra, Richard1 aWare, Doreen1 aWilkins, Olivia1 aWilliams, Cranos1 aBrady, Siobhan, M. uhttp://www.plantphysiol.org/content/175/4/149902614nas a2200517 4500008004100000020004600041245014500087210006900232260001200301300001200313490000700325520091000332653004701242653005901289653002401348653003801372653002901410653001701439653002001456653002101476653002001497653003601517653003301553653003001586653004301616653004101659653004801700653003301748100001901781700001501800700001801815700001101833700001801844700001301862700002001875700001401895700001401909700002101923700001401944700002201958700001501980700001501995700001802010700001902028856004902047 2016 eng d a1878-1551 (Electronic)1534-5807 (Linking)00aEstablishment of Expression in the SHORTROOT-SCARECROW Transcriptional Cascade through Opposing Activities of Both Activators and Repressors0 aEstablishment of Expression in the SHORTROOTSCARECROW Transcript c12/2016 a585-5960 v393 a

Tissue-specific gene expression is often thought to arise from spatially restricted transcriptional cascades. However, it is unclear how expression is established at the top of these cascades in the absence of pre-existing specificity. We generated a transcriptional network to explore how transcription factor expression is established in the Arabidopsis thaliana root ground tissue. Regulators of the SHORTROOT-SCARECROW transcriptional cascade were validated in planta. At the top of this cascade, we identified both activators and repressors of SHORTROOT. The aggregate spatial expression of these regulators is not sufficient to predict transcriptional specificity. Instead, modeling, transcriptional reporters, and synthetic promoters support a mechanism whereby expression at the top of the SHORTROOT-SCARECROW cascade is established through opposing activities of activators and repressors.

10aArabidopsis Proteins/ genetics/ metabolism10aArabidopsis/ genetics/growth & development/ metabolism10aComputer Simulation10aGene Expression Regulation, Plant10aGene Regulatory Networks10aGenes, Plant10aGenes, Reporter10aGenes, Synthetic10aModels, Genetic10aPlant Roots/cytology/metabolism10aPlants, Genetically Modified10aPromoter Regions, Genetic10aRepressor Proteins/genetics/metabolism10aTrans-Activators/genetics/metabolism10aTranscription Factors/ genetics/ metabolism10aTwo-Hybrid System Techniques1 aSparks, E., E.1 aDrapek, C.1 aGaudinier, A.1 aLi, S.1 aAnsariola, M.1 aShen, N.1 aHennacy, J., H.1 aZhang, J.1 aTurco, G.1 aPetricka, J., J.1 aForet, J.1 aHartemink, A., J.1 aGordan, R.1 aMegraw, M.1 aBrady, S., M.1 aBenfey, P., N. uhttps://doi.org/10.1016/j.devcel.2016.09.03101715nas a2200253 4500008004100000022001400041245011200055210006900167260001300236300001100249490000700260520091500267653002701182653002501209653002101234653003401255653001501289653002601304100002201330700002101352700001801373700002101391856004901412 2015 eng d a1879-035600aAlternative splicing in plants: directing traffic at the crossroads of adaptation and environmental stress.0 aAlternative splicing in plants directing traffic at the crossroa c2015 Apr a125-350 v243 a

In recent years, high-throughput sequencing-based analysis of plant transcriptomes has suggested that up to ∼60% of plant gene loci encode alternatively spliced mature transcripts. These studies have also revealed that alternative splicing in plants can be regulated by cell type, developmental stage, the environment, and the circadian clock. Alternative splicing is coupled to RNA surveillance and processing mechanisms, including nonsense mediated decay. Recently, non-protein-coding transcripts have also been shown to undergo alternative splicing. These discoveries collectively describe a robust system of post-transcriptional regulatory feedback loops which influence RNA abundance. In this review, we summarize recent studies describing the specific roles alternative splicing and RNA surveillance play in plant adaptation to environmental stresses and the regulation of the circadian clock.

10aAdaptation, Biological10aAlternative Splicing10aCircadian Clocks10aPlant Physiological Phenomena10aRNA, Plant10aStress, Physiological1 aFilichkin, Sergei1 aPriest, Henry, D1 aMegraw, Molly1 aMockler, Todd, C uhttps://megraw.cgrb.oregonstate.edu/node/31402503nas a2200325 4500008004100000022001400041245012000055210006900175260001300244300001100257490000600268520148900274653002501763653001601788653002501804653002101829653003801850653001201888653003301900100002501933700002101958700002801979700002002007700001902027700002502046700001802071700001802089700002102107856004902128 2015 eng d a1752-986700aEnvironmental stresses modulate abundance and timing of alternatively spliced circadian transcripts in Arabidopsis.0 aEnvironmental stresses modulate abundance and timing of alternat c2015 Feb a207-270 v83 a

Environmental stresses profoundly altered accumulation of nonsense mRNAs including intron-retaining (IR) transcripts in Arabidopsis. Temporal patterns of stress-induced IR mRNAs were dissected using both oscillating and non-oscillating transcripts. Broad-range thermal cycles triggered a sharp increase in the long IR CCA1 isoforms and altered their phasing to different times of day. Both abiotic and biotic stresses such as drought or Pseudomonas syringae infection induced a similar increase. Thermal stress induced a time delay in accumulation of CCA1 I4Rb transcripts, whereas functional mRNA showed steady oscillations. Our data favor a hypothesis that stress-induced instabilities of the central oscillator can be in part compensated through fluctuations in abundance and out-of-phase oscillations of CCA1 IR transcripts. Taken together, our results support a concept that mRNA abundance can be modulated through altering ratios between functional and nonsense/IR transcripts. SR45 protein specifically bound to the retained CCA1 intron in vitro, suggesting that this splicing factor could be involved in regulation of intron retention. Transcriptomes of nonsense-mediated mRNA decay (NMD)-impaired and heat-stressed plants shared a set of retained introns associated with stress- and defense-inducible transcripts. Constitutive activation of certain stress response networks in an NMD mutant could be linked to disequilibrium between functional and nonsense mRNAs.

10aAlternative Splicing10aArabidopsis10aArabidopsis Proteins10aCircadian Clocks10aGene Expression Regulation, Plant10aIntrons10aNonsense Mediated mRNA Decay1 aFilichkin, Sergei, A1 aCumbie, Jason, S1 aDharmawardhana, Palitha1 aJaiswal, Pankaj1 aChang, Jeff, H1 aPalusa, Saiprasad, G1 aReddy, A, S N1 aMegraw, Molly1 aMockler, Todd, C uhttps://megraw.cgrb.oregonstate.edu/node/31502171nas a2200217 4500008004100000022001400041245012000055210006900175260001500244520145100259100002501710700002101735700002701756700002001783700001901803700002501822700001801847700001801865700002101883856004901904 2014 eng d a1752-986700aEnvironmental Stresses Modulate Abundance and Timing of Alternatively Spliced Circadian Transcripts in Arabidopsis.0 aEnvironmental Stresses Modulate Abundance and Timing of Alternat c2014 Nov 33 a

Environmental stresses profoundly altered accumulation of nonsense mRNAs including intron retaining (IR) transcripts in Arabidopsis. Temporal patterns of stress-induced IR mRNAs were dissected using both oscillating and non-oscillating transcripts. Broad range thermal cycles triggered a sharp increase in the long intron retaining CCA1 isoforms and altered their phasing to different times of day. Both abiotic and biotic stresses such as drought or P. syringae infection induced similar increase. Thermal stress induced a time delay in accumulation of CCA1 I4Rb transcripts whereas functional mRNA showed steady oscillations. Our data favor a hypothesis that stress-induced instabilities of the central oscillator can be in part compensated through fluctuations in abundance and out of phase oscillations of CCA1 IR transcripts. Altogether, our results support a concept that mRNA abundance can be modulated through altering ratios between functional and nonsense/IR transcripts. SR45 protein specifically bound to the retained CCA1 intron in vitro, suggesting that this splicing factor could be involved in regulation of intron retention. Transcriptomes of NMD-impaired and heat-stressed plants shared a set of retained introns associated with stress- and defense-inducible transcripts. Constitutive activation of certain stress response networks in an NMD mutant could be linked to disequilibrium between functional and nonsense mRNAs.

1 aFilichkin, Sergei, A1 aCumbie, Jason, S1 aDharmawadhana, Palitha1 aJaiswal, Pankaj1 aChang, Jeff, H1 aPalusa, Saiprasad, G1 aReddy, A, S N1 aMegraw, Molly1 aMockler, Todd, C uhttps://megraw.cgrb.oregonstate.edu/node/31702911nas a2200457 4500008004100000022001400041245011200055210006900167260001300236300001200249490000700261520157400268653001601842653002501858653001801883653002101901653001501922653003801937653001801975653002001993653002202013653001602035653003002051653001902081653001502100653002702115653002402142653001302166653002602179653003402205100001602239700002102255700002302276700001302299700002002312700001702332700002202349700001502371700001802386856004902404 2014 eng d a1532-298X00aPaired-end analysis of transcription start sites in Arabidopsis reveals plant-specific promoter signatures.0 aPairedend analysis of transcription start sites in Arabidopsis r c2014 Jul a2746-600 v263 a

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]

10aArabidopsis10aArabidopsis Proteins10aBinding Sites10aCluster Analysis10aDNA, Plant10aGene Expression Regulation, Plant10aGenome, Plant10aModels, Genetic10aNucleotide Motifs10aPlant Roots10aPromoter Regions, Genetic10aRNA, Messenger10aRNA, Plant10aSequence Analysis, DNA10aSpecies Specificity10aTATA Box10aTranscription Factors10aTranscription Initiation Site1 aMorton, Taj1 aPetricka, Jalean1 aCorcoran, David, L1 aLi, Song1 aWinter, Cara, M1 aCarda, Alexa1 aBenfey, Philip, N1 aOhler, Uwe1 aMegraw, Molly uhttps://megraw.cgrb.oregonstate.edu/node/31902379nas a2200433 4500008004100000022001400041245006200055210005700117260001500174300001100189490000800200520113300208653001601341653002501357653001801382653002701400653001601427653003001443653001601473653003301489653002701522653003201549653001301581653001501594653001501609653002901624100002401653700002301677700001801700700002701718700001901745700002101764700002301785700001501808700002801823700002301851700002201874856004901896 2012 eng d a1091-649000aThe protein expression landscape of the Arabidopsis root.0 aprotein expression landscape of the Arabidopsis root c2012 May 1 a6811-80 v1093 a

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.

10aArabidopsis10aArabidopsis Proteins10aBase Sequence10aChromatography, Liquid10aDNA Primers10aGene Expression Profiling10aPlant Roots10aPlants, Genetically Modified10aProtein Array Analysis10aProtein Interaction Mapping10aProteome10aProteomics10aRNA, Plant10aTandem Mass Spectrometry1 aPetricka, Jalean, J1 aSchauer, Monica, A1 aMegraw, Molly1 aBreakfield, Natalie, W1 aThompson, Will1 aGeorgiev, Stoyan1 aSoderblom, Erik, J1 aOhler, Uwe1 aMoseley, Martin, Arthur1 aGrossniklaus, Ueli1 aBenfey, Philip, N uhttps://megraw.cgrb.oregonstate.edu/node/32102129nas a2200421 4500008004100000022001400041245007500055210006900130260001300199300001200212490000700224520091800231653002801149653001501177653001201192653002101204653002601225653002301251653002801274653001101302653003801313653001301351653000901364653001401373653003601387653001301423653002601436100002401462700002401486700002301510700001901533700002401552700001801576700001601594700001801610700003001628856004901658 2010 eng d a1362-496200amiRGen 2.0: a database of microRNA genomic information and regulation.0 amiRGen 20 a database of microRNA genomic information and regulat c2010 Jan aD137-410 v383 a

MicroRNAs are small, non-protein coding RNA molecules known to regulate the expression of genes by binding to the 3'UTR region of mRNAs. MicroRNAs are produced from longer transcripts which can code for more than one mature miRNAs. miRGen 2.0 is a database that aims to provide comprehensive information about the position of human and mouse microRNA coding transcripts and their regulation by transcription factors, including a unique compilation of both predicted and experimentally supported data. Expression profiles of microRNAs in several tissues and cell lines, single nucleotide polymorphism locations, microRNA target prediction on protein coding genes and mapping of miRNA targets of co-regulated miRNAs on biological pathways are also integrated into the database and user interface. The miRGen database will be continuously maintained and freely available at http://www.microrna.gr/mirgen/.

10a3' Untranslated Regions10aAlgorithms10aAnimals10aCell Line, Tumor10aComputational Biology10aDatabases, Genetic10aDatabases, Nucleic Acid10aHumans10aInformation Storage and Retrieval10aInternet10aMice10aMicroRNAs10aPolymorphism, Single Nucleotide10aSoftware10aTranscription Factors1 aAlexiou, Panagiotis1 aVergoulis, Thanasis1 aGleditzsch, Martin1 aPrekas, George1 aDalamagas, Theodore1 aMegraw, Molly1 aGrosse, Ivo1 aSellis, Timos1 aHatzigeorgiou, Artemis, G uhttps://megraw.cgrb.oregonstate.edu/node/32402836nas a2200337 4500008004100000022001400041245008700055210006900142260001300211300001100224490000700235520183700242653002102079653002302100653000802123653003102131653001802162653001102180653003002191653002202221653001302243653002602256653003402282653002702316100001802343700002202361700002102383700001502404700003002419856004902449 2009 eng d a1088-905100aA transcription factor affinity-based code for mammalian transcription initiation.0 atranscription factor affinitybased code for mammalian transcript c2009 Apr a644-560 v193 a

The recent arrival of large-scale cap analysis of gene expression (CAGE) data sets in mammals provides a wealth of quantitative information on coding and noncoding RNA polymerase II transcription start sites (TSS). Genome-wide CAGE studies reveal that a large fraction of TSS exhibit peaks where the vast majority of associated tags map to a particular location ( approximately 45%), whereas other active regions contain a broader distribution of initiation events. The presence of a strong single peak suggests that transcription at these locations may be mediated by position-specific sequence features. We therefore propose a new model for single-peaked TSS based solely on known transcription factors (TFs) and their respective regions of positional enrichment. This probabilistic model leads to near-perfect classification results in cross-validation (auROC = 0.98), and performance in genomic scans demonstrates that TSS prediction with both high accuracy and spatial resolution is achievable for a specific but large subgroup of mammalian promoters. The interpretable model structure suggests a DNA code in which canonical sequence features such as TATA-box, Initiator, and GC content do play a significant role, but many additional TFs show distinct spatial biases with respect to TSS location and are important contributors to the accurate prediction of single-peak transcription initiation sites. The model structure also reveals that CAGE tag clusters distal from annotated gene starts have distinct characteristics compared to those close to gene 5'-ends. Using this high-resolution single-peak model, we predict TSS for approximately 70% of mammalian microRNAs based on currently available data.

[Links to Tools and Supplementary Materials]

10aBase Composition10aDatabases, Genetic10aDNA10aGene Expression Regulation10aGenome, Human10aHumans10aPromoter Regions, Genetic10aRNA Polymerase II10aTATA Box10aTranscription Factors10aTranscription Initiation Site10aTranscription, Genetic1 aMegraw, Molly1 aPereira, Fernando1 aJensen, Shane, T1 aOhler, Uwe1 aHatzigeorgiou, Artemis, G uhttps://megraw.cgrb.oregonstate.edu/node/326