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/pld3.10900821nas a2200289 4500008004100000245007200041210006900113260001200182300000900194490000700203100001000210700001700220700001800237700001600255700001700271700001100288700001800299700001500317700001400332700001600346700001600362700001400378700001500392700001400407700002700421856008300448 2019 eng d00aPlantSimLab-a modeling and simulation web tool for plant biologists0 aPlantSimLaba modeling and simulation web tool for plant biologis c12/2019 a1-110 v201 aHa, S1 aDimitrova, E1 aHoops, Stefan1 aAltarawy, D1 aAnsariola, M1 aDeb, D1 aGlazebrook, J1 aHillmer, R1 aShahin, H1 aKatagiri, F1 aMcDowell, J1 aMegraw, M1 aSetubal, J1 aTyler, BM1 aLaubenbacher, Reinhard uhttps://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-3094-902308nas a2200169 4500008004100000245013500041210006900176260001200245300001200257490000800269520169800277100002501975700002102000700002302021700001802044856007602062 2018 eng d00aIdentification of transcription factors from NF-Y, NAC, and SPL families responding to osmotic stress in multiple tomato varieties0 aIdentification of transcription factors from NFY NAC and SPL fam c09/2018 a441-4500 v2743 a

Identifying osmotic stress-responsive transcription factors (TFs) can facilitate discovery of master regulators mediating salt and/or drought tolerance. To date, few RNA-seq datasets for high resolution time course of salt or drought stress treatments are publicly available for certain crop species. However, such datasets may be available for other crops, and in combination with orthology analysis may be used to infer candidate osmotic stress regulators across distantly related species. Here, we demonstrate the utility of this approach for identification and validation of osmotic stress-responsive transcription factors in tomato. First, we developed physiologically calibrated salt and dehydration-responsive systems for tomato cultivars using real time measurements of transpiration rate and photosynthetic efficiency. Next, we identified differentially expressed TFs in rice using raw RNA-seq datasets for a publicly available salt stress time course. Putative salt stress-responsive TFs in tomato were then inferred based on their orthology with the transcription factors upregulated by salt in rice. Finally, using our osmotic stress system, we experimentally validated stress-responsive expression of predicted tomato candidates representing NUCLEAR FACTOR Y, SQUAMOSA PROMOTER BINDING, and NAC domain TF families. Quantification of transcript copy numbers confirmed that mRNAs encoding all three TFs were strongly upregulated not only by salt but also by drought stress. Induction by both salt and dehydration occurred in a temporal manner across diverse tomato cultivars, suggesting that the identified TFs may play important roles in regulating osmotic stress responses.

1 aFilichkin, Sergei, A1 aAnsariola, Mitra1 aFraser, Valerie, N1 aMegraw, Molly uhttps://www.sciencedirect.com/science/article/abs/pii/S016894521830353401946nas a2200157 4500008004100000245007200041210006900113260001200182300001400194490000700208520144400215100002101659700001801680700002001698856007001718 2018 eng d00aIndeCut evaluates performance of network motif discovery algorithms0 aIndeCut evaluates performance of network motif discovery algorit c05/2018 a1514-15210 v343 a
Motivation
Genomic networks represent a complex map of molecular interactions which are descriptive of the biological processes occurring in living cells. Identifying the small over-represented circuitry patterns in these networks helps generate hypotheses about the functional basis of such complex processes. Network motif discovery is a systematic way of achieving this goal. However, a reliable network motif discovery outcome requires generating random background networks which are the result of a uniform and independent graph sampling method. To date, there has been no method to numerically evaluate whether any network motif discovery algorithm performs as intended on realistically sized datasets—thus it was not possible to assess the validity of resulting network motifs.
 
Results
In this work, we present IndeCut, the first method to date that characterizes network motif finding algorithm performance in terms of uniform sampling on realistically sized networks. We demonstrate that it is critical to use IndeCut prior to running any network motif finder for two reasons. First, IndeCut indicates the number of samples needed for a tool to produce an outcome that is both reproducible and accurate. Second, IndeCut allows users to choose the tool that generates samples in the most independent fashion for their network of interest among many available options.
1 aAnsariola, Mitra1 aMegraw, Molly1 aKoslicki, David uhttps://academic.oup.com/bioinformatics/article/34/9/1514/472178501333nas a2200145 4500008004100000245008400041210006900125260001200194300001200206490000900218520084900227100002501076700001801101856006801119 2018 eng d00aNanoCAGE-XL: An Approach to High-Confidence Transcription Start Site Sequencing0 aNanoCAGEXL An Approach to HighConfidence Transcription Start Sit c07/2018 a225-2370 v18303 a

Identifying the transcription start sites (TSS) of genes is essential for characterizing promoter regions. Several protocols have been developed to capture the 5′ end of transcripts via Cap-Analysis of Gene Expression (CAGE) or linker-ligation strategies such as Paired-End Analysis of Transcription Start Sites (PEAT), but often require large amounts of tissue. More recently, nanoCAGE was developed for sequencing on the Illumina GAIIx to overcome this limitation. In this chapter, we present the nanoCAGE-XL protocol, the first publicly available adaptation of nanoCAGE for sequencing on recent ultra-high-throughput platforms such as Illumina HiSeq-2000. NanoCAGE-XL provides a method for precise transcription start site identification in large eukaryotic genomes, even in cases where input total RNA quantity is very limited.

1 aIvanchenko, Maria, G1 aMegraw, Molly uhttps://link.springer.com/protocol/10.1007/978-1-4939-8657-6_1301445nas a2200145 4500008004100000020004600041245009100087210006900178300001200247490000900259520092600268100002201194700001501216856006801231 2017 eng d a1940-6029 (Electronic)1064-3745 (Linking)00aDNase I SIM: A Simplified In-Nucleus Method for DNase I Hypersensitive Site Sequencing0 aDNase I SIM A Simplified InNucleus Method for DNase I Hypersensi a141-1540 v16293 a

Identifying cis-regulatory elements is critical in understanding the direct and indirect interactions that occur within gene regulatory networks. Current approaches include DNase-seq, a technique that combines sensitivity to the nonspecific endonuclease DNase I with high-throughput sequencing to identify regions of regulatory DNA on a genome-wide scale. Yet, challenges still remain in processing recalcitrant tissues that have low DNA content. Here, we describe DNase I SIM (for Simplified In-nucleus Method), a protocol that simplifies and facilitates generation of DNase-seq libraries from plant tissues for high-resolution mapping of DNase I hypersensitive sites. By removing steps requiring the use of gel agarose plugs in DNase-seq, DNase I SIM reduces the time required to perform the protocol by at least 2 days, while also making possible the processing of difficult plant tissues including plant roots.

1 aFilichkin, S., A.1 aMegraw, M. uhttps://link.springer.com/protocol/10.1007/978-1-4939-7125-1_1002932nas 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.2016.09.03102264nas a2200181 4500008004100000022001400041245010600055210006900161260001300230300001200243490000700255520168200262100001801944700002101962700002501983700002502008856004902033 2016 eng d a1532-298X00aSmall Genetic Circuits and MicroRNAs: Big Players in Polymerase II Transcriptional Control in Plants.0 aSmall Genetic Circuits and MicroRNAs Big Players in Polymerase I c2016 Feb a286-3030 v283 a

RNA Polymerase II (Pol II) regulatory cascades involving transcription factors (TFs) and their targets orchestrate the genetic circuitry of every eukaryotic organism. In order to understand how these cascades function, they can be dissected into small genetic networks, each containing just a few Pol II transcribed genes, that generate specific signal-processing outcomes. Small RNA regulatory circuits involve direct regulation of a small RNA by a TF and/or direct regulation of a TF by a small RNA and have been shown to play unique roles in many organisms. Here, we will focus on small RNA regulatory circuits containing Pol II transcribed microRNAs (miRNAs). While the role of miRNA-containing regulatory circuits as modular building blocks for the function of complex networks has long been on the forefront of studies in the animal kingdom, plant studies are poised to take a lead role in this area because of their advantages in probing transcriptional and posttranscriptional control of Pol II genes. The relative simplicity of tissue- and cell-type organization, miRNA targeting, and genomic structure make the Arabidopsis thaliana plant model uniquely amenable for small RNA regulatory circuit studies in a multicellular organism. In this Review, we cover analysis, tools, and validation methods for probing the component interactions in miRNA-containing regulatory circuits. We then review the important roles that plant miRNAs are playing in these circuits and summarize methods for the identification of small genetic circuits that strongly influence plant function. We conclude by noting areas of opportunity where new plant studies are imminently needed.

1 aMegraw, Molly1 aCumbie, Jason, S1 aIvanchenko, Maria, G1 aFilichkin, Sergei, A uhttps://megraw.cgrb.oregonstate.edu/node/31201715nas 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/31402854nas a2200373 4500008004100000022001400041245012300055210006900178260001600247300001100263490000800274520174600282653001602028653002502044653001802069653002302087653002802110653001902138653001602157653001702173100002502190700001802215700001802233700001902251700001602270700002102286700002102307700001802328700002202346700002502368700001802393700002002411856004902431 2015 eng d a1477-912900aThe cyclophilin A DIAGEOTROPICA gene affects auxin transport in both root and shoot to control lateral root formation.0 acyclophilin A DIAGEOTROPICA gene affects auxin transport in both c2015 Feb 15 a712-210 v1423 a

Cyclophilin A is a conserved peptidyl-prolyl cis-trans isomerase (PPIase) best known as the cellular receptor of the immunosuppressant cyclosporine A. Despite significant effort, evidence of developmental functions of cyclophilin A in non-plant systems has remained obscure. Mutations in a tomato (Solanum lycopersicum) cyclophilin A ortholog, DIAGEOTROPICA (DGT), have been shown to abolish the organogenesis of lateral roots; however, a mechanistic explanation of the phenotype is lacking. Here, we show that the dgt mutant lacks auxin maxima relevant to priming and specification of lateral root founder cells. DGT is expressed in shoot and root, and localizes to both the nucleus and cytoplasm during lateral root organogenesis. Mutation of ENTIRE/IAA9, a member of the auxin-responsive Aux/IAA protein family of transcriptional repressors, partially restores the inability of dgt to initiate lateral root primordia but not the primordia outgrowth. By comparison, grafting of a wild-type scion restores the process of lateral root formation, consistent with participation of a mobile signal. Antibodies do not detect movement of the DGT protein into the dgt rootstock; however, experiments with radiolabeled auxin and an auxin-specific microelectrode demonstrate abnormal auxin fluxes. Functional studies of DGT in heterologous yeast and tobacco-leaf auxin-transport systems demonstrate that DGT negatively regulates PIN-FORMED (PIN) auxin efflux transporters by affecting their plasma membrane localization. Studies in tomato support complex effects of the dgt mutation on PIN expression level, expression domain and plasma membrane localization. Our data demonstrate that DGT regulates auxin transport in lateral root formation.

10aArabidopsis10aBiological Transport10aCyclophilin A10aIndoleacetic Acids10aLycopersicon esculentum10aPlant Proteins10aPlant Roots10aPlant Shoots1 aIvanchenko, Maria, G1 aZhu, Jinsheng1 aWang, Bangjun1 aMedvecká, Eva1 aDu, Yunlong1 aAzzarello, Elisa1 aMancuso, Stefano1 aMegraw, Molly1 aFilichkin, Sergei1 aDubrovsky, Joseph, G1 aFriml, Jiří1 aGeisler, Markus uhttps://megraw.cgrb.oregonstate.edu/node/31602503nas 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/31501941nas a2200169 4500008004100000022001400041245013400055210006900189260000900258300000700267490000700274520137700281100002101658700002501679700001801704856004901722 2015 eng d a1746-481100aImproved DNase-seq protocol facilitates high resolution mapping of DNase I hypersensitive sites in roots in Arabidopsis thaliana.0 aImproved DNaseseq protocol facilitates high resolution mapping o c2015 a420 v113 a

BACKGROUND: Identifying cis-regulatory elements is critical in understanding the direct and indirect regulatory mechanisms of gene expression. Current approaches include DNase-seq, a technique that combines sensitivity to the nonspecific endonuclease DNase I with high throughput sequencing to identify regions of regulatory DNA on a genome-wide scale. While this method was originally developed for human cell lines, later adaptations made the processing of plant tissues possible. Challenges still remain in processing recalcitrant tissues that have low DNA content.

RESULTS: By removing steps requiring the use of gel agarose plugs in DNase-seq, we were able to significantly reduce the time required to perform the protocol by at least 2 days, while also making possible the processing of difficult plant tissues. We refer to this simplified protocol as DNase I SIM (for simplified in-nucleus method). We were able to successfully create DNase-seq libraries for both leaf and root tissues in Arabidopsis using DNase I SIM.

CONCLUSION: This protocol simplifies and facilitates generation of DNase-seq libraries from plant tissues for high resolution mapping of DNase I hypersensitive sites.

[Link to Protocol, Additional Data, and Supplementary Materials]

1 aCumbie, Jason, S1 aFilichkin, Sergei, A1 aMegraw, Molly uhttps://megraw.cgrb.oregonstate.edu/node/31002178nas a2200277 4500008004100000022001400041245011900055210006900174260000900243300000800252490000700260520133000267653001601597653001701613653001801630653001901648653001601667653003001683653002701713653001301740653003401753100002101787700002501808700001801833856004901851 2015 eng d a1471-216400aNanoCAGE-XL and CapFilter: an approach to genome wide identification of high confidence transcription start sites.0 aNanoCAGEXL and CapFilter an approach to genome wide identificati c2015 a5970 v163 a

BACKGROUND: Identifying the transcription start sites (TSS) of genes is essential for characterizing promoter regions. Several protocols have been developed to capture the 5' end of transcripts via Cap Analysis of Gene Expression (CAGE) or linker-ligation strategies such as Paired-End Analysis of Transcription Start Sites (PEAT), but often require large amounts of tissue. More recently, nanoCAGE was developed for sequencing on the Illumina GAIIx to overcome these difficulties.

RESULTS: Here we present the first publicly available adaptation of nanoCAGE for sequencing on recent ultra-high throughput platforms such as Illumina HiSeq-2000, and CapFilter, a computational pipeline that greatly increases confidence in TSS identification. We report excellent gene coverage, reproducibility, and precision in transcription start site discovery for samples from Arabidopsis thaliana roots.

CONCLUSION: nanoCAGE-XL together with CapFilter allows for genome wide identification of high confidence transcription start sites in large eukaryotic genomes.

[Link to Protocol, Additional Data, and Supplementary Materials]

[Link to CapFilter Software]

10aArabidopsis10aGenes, Plant10aGenome, Plant10aNanotechnology10aPlant Roots10aPromoter Regions, Genetic10aSequence Analysis, DNA10aSoftware10aTranscription Initiation Site1 aCumbie, Jason, S1 aIvanchenko, Maria, G1 aMegraw, Molly uhttps://megraw.cgrb.oregonstate.edu/node/31102325nas a2200265 4500008004100000022001400041245007400055210006900129260001500198300001200213490000700225520152900232653001501761653001301776653002101789653003401810653002701844653001301871653003401884653003801918100001601956700002001972700001801992856004902010 2015 eng d a1367-481100aTIPR: transcription initiation pattern recognition on a genome scale.0 aTIPR transcription initiation pattern recognition on a genome sc c2015 Dec 1 a3725-320 v313 a

MOTIVATION: The computational identification of gene transcription start sites (TSSs) can provide insights into the regulation and function of genes without performing expensive experiments, particularly in organisms with incomplete annotations. High-resolution general-purpose TSS prediction remains a challenging problem, with little recent progress on the identification and differentiation of TSSs which are arranged in different spatial patterns along the chromosome.

RESULTS: In this work, we present the Transcription Initiation Pattern Recognizer (TIPR), a sequence-based machine learning model that identifies TSSs with high accuracy and resolution for multiple spatial distribution patterns along the genome, including broadly distributed TSS patterns that have previously been difficult to characterize. TIPR predicts not only the locations of TSSs but also the expected spatial initiation pattern each TSS will form along the chromosome-a novel capability for TSS prediction algorithms. As spatial initiation patterns are associated with spatiotemporal expression patterns and gene function, this capability has the potential to improve gene annotations and our understanding of the regulation of transcription initiation. The high nucleotide resolution of this model locates TSSs within 10 nucleotides or less on average.

CONTACT: megrawm@science.oregonstate.edu.

[Software and Supplementary Materials Link]

10aAlgorithms10aGenomics10aMachine Learning10aMolecular Sequence Annotation10aSequence Analysis, DNA10aSoftware10aTranscription Initiation Site10aTranscription Initiation, Genetic1 aMorton, Taj1 aWong, Weng-Keen1 aMegraw, Molly uhttps://megraw.cgrb.oregonstate.edu/node/31302735nas a2200301 4500008004100000022001400041245016300055210006900218260001300287300001300300490000700313520173600320653001002056653003002066653003802096653004402134653002802178653001702206653002702223653001002250100002602260700002102286700001602307700002102323700001802344700002202362856004902384 2014 eng d a1460-243100aA comparative study of ripening among berries of the grape cluster reveals an altered transcriptional programme and enhanced ripening rate in delayed berries.0 acomparative study of ripening among berries of the grape cluster c2014 Nov a5889-9020 v653 a

Transcriptional studies in relation to fruit ripening generally aim to identify the transcriptional states associated with physiological ripening stages and the transcriptional changes between stages within the ripening programme. In non-climacteric fruits such as grape, all ripening-related genes involved in this programme have not been identified, mainly due to the lack of mutants for comparative transcriptomic studies. A feature in grape cluster ripening (Vitis vinifera cv. Pinot noir), where all berries do not initiate the ripening at the same time, was exploited to study their shifted ripening programmes in parallel. Berries that showed marked ripening state differences in a véraison-stage cluster (ripening onset) ultimately reached similar ripeness states toward maturity, indicating the flexibility of the ripening programme. The expression variance between these véraison-stage berry classes, where 11% of the genes were found to be differentially expressed, was reduced significantly toward maturity, resulting in the synchronization of their transcriptional states. Defined quantitative expression changes (transcriptional distances) not only existed between the véraison transitional stages, but also between the véraison to maturity stages, regardless of the berry class. It was observed that lagging berries complete their transcriptional programme in a shorter time through altered gene expressions and ripening-related hormone dynamics, and enhance the rate of physiological ripening progression. Finally, the reduction in expression variance of genes can identify new genes directly associated with ripening and also assess the relevance of gene activity to the phase of the ripening programme.

10aFruit10aGene Expression Profiling10aGene Expression Regulation, Plant10aOligonucleotide Array Sequence Analysis10aPlant Growth Regulators10aTime Factors10aTranscription, Genetic10aVitis1 aGouthu, Satyanarayana1 aO'Neil, Shawn, T1 aDi, Yanming1 aAnsarolia, Mitra1 aMegraw, Molly1 aDeluc, Laurent, G uhttps://megraw.cgrb.oregonstate.edu/node/31802171nas 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/31901718nas a2200325 4500008004100000022001400041245012600055210006900181260000900250300000800259490000700267520073000274653001501004653001201019653001601031653002601047653002801073653003101101653002901132653001101161653001401172653003401186653003001220653001301250653002601263100001801289700002101307700001501328856004901343 2013 eng d a1474-760X00aSustained-input switches for transcription factors and microRNAs are central building blocks of eukaryotic gene circuits.0 aSustainedinput switches for transcription factors and microRNAs  c2013 aR850 v143 a

WaRSwap is a randomization algorithm that for the first time provides a practical network motif discovery method for large multi-layer networks, for example those that include transcription factors, microRNAs, and non-regulatory protein coding genes. The algorithm is applicable to systems with tens of thousands of genes, while accounting for critical aspects of biological networks, including self-loops, large hubs, and target rearrangements. We validate WaRSwap on a newly inferred regulatory network from Arabidopsis thaliana, and compare outcomes on published Drosophila and human networks. Specifically, sustained input switches are among the few over-represented circuits across this diverse set of eukaryotes.

10aAlgorithms10aAnimals10aArabidopsis10aComputational Biology10aDrosophila melanogaster10aGene Expression Regulation10aGene Regulatory Networks10aHumans10aMicroRNAs10aMolecular Sequence Annotation10aNucleic Acid Conformation10aSoftware10aTranscription Factors1 aMegraw, Molly1 aMukherjee, Sayan1 aOhler, Uwe uhttps://megraw.cgrb.oregonstate.edu/node/32002379nas 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/32102390nas a2200433 4500008004100000022001400041245007000055210006600125260001600191300000800207490000600215520115000221653001601371653002501387653003001412653002901442653001401471653001601485653003101501653002001532653002601552653003301578100002201611700001801633700001801651700002501669700001601694700001901710700001601729700001501745700002901760700001501789700002201804700001501826700001701841700002701858700002201885856004901907 2011 eng d a1744-429200aA stele-enriched gene regulatory network in the Arabidopsis root.0 asteleenriched gene regulatory network in the Arabidopsis root c2011 Jan 18 a4590 v73 a

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.

10aArabidopsis10aArabidopsis Proteins10aGene Expression Profiling10aGene Regulatory Networks10aMicroRNAs10aPlant Roots10aReproducibility of Results10aSystems Biology10aTranscription Factors10aTwo-Hybrid System Techniques1 aBrady, Siobhan, M1 aZhang, Lifang1 aMegraw, Molly1 aMartinez, Natalia, J1 aJiang, Eric1 aYi, Charles, S1 aLiu, Weilin1 aZeng, Anna1 aTaylor-Teeples, Mallorie1 aKim, Dahae1 aAhnert, Sebastian1 aOhler, Uwe1 aWare, Doreen1 aWalhout, Albertha, J M1 aBenfey, Philip, N uhttps://megraw.cgrb.oregonstate.edu/node/32202616nas a2200445 4500008004100000022001400041245012900055210006900184260001600253300001300269490000800282520127800290653002101568653003401589653004001623653001901663653002501682653001101707653002901718653001401747653002101761653001601782653001501798653002101813653001901834653001801853100002001871700002201891700002301913700002401936700001801960700002701978700001702005700001802022700002102040700001802061700002002079700002202099856004902121 2010 eng d a1083-351X00aEditing of Epstein-Barr virus-encoded BART6 microRNAs controls their dicer targeting and consequently affects viral latency.0 aEditing of EpsteinBarr virusencoded BART6 microRNAs controls the c2010 Oct 22 a33358-700 v2853 a

Certain primary transcripts of miRNA (pri-microRNAs) undergo RNA editing that converts adenosine to inosine. The Epstein-Barr virus (EBV) genome encodes multiple microRNA genes of its own. Here we report that primary transcripts of ebv-miR-BART6 (pri-miR-BART6) are edited in latently EBV-infected cells. Editing of wild-type pri-miR-BART6 RNAs dramatically reduced loading of miR-BART6-5p RNAs onto the microRNA-induced silencing complex. Editing of a mutation-containing pri-miR-BART6 found in Daudi Burkitt lymphoma and nasopharyngeal carcinoma C666-1 cell lines suppressed processing of miR-BART6 RNAs. Most importantly, miR-BART6-5p RNAs silence Dicer through multiple target sites located in the 3'-UTR of Dicer mRNA. The significance of miR-BART6 was further investigated in cells in various stages of latency. We found that miR-BART6-5p RNAs suppress the EBNA2 viral oncogene required for transition from immunologically less responsive type I and type II latency to the more immunoreactive type III latency as well as Zta and Rta viral proteins essential for lytic replication, revealing the regulatory function of miR-BART6 in EBV infection and latency. Mutation and A-to-I editing appear to be adaptive mechanisms that antagonize miR-BART6 activities.

10aCell Line, Tumor10aEpstein-Barr Virus Infections10aEpstein-Barr Virus Nuclear Antigens10aGene Silencing10aHerpesvirus 4, Human10aHumans10aImmediate-Early Proteins10aMicroRNAs10aRibonuclease III10aRNA Editing10aRNA, Viral10aTrans-Activators10aViral Proteins10aVirus Latency1 aIizasa, Hisashi1 aWulff, Bjorn-Erik1 aAlla, Nageswara, R1 aMaragkakis, Manolis1 aMegraw, Molly1 aHatzigeorgiou, Artemis1 aIwakiri, Dai1 aTakada, Kenzo1 aWiedmer, Andreas1 aShowe, Louise1 aLieberman, Paul1 aNishikura, Kazuko uhttps://megraw.cgrb.oregonstate.edu/node/32301594nas a2200193 4500008004100000022001400041245003200055210003100087260000900118300001100127490000800138520108700146653001401233653003001247653002601277100001801303700003001321856004901351 2010 eng d a1940-602900aMicroRNA promoter analysis.0 aMicroRNA promoter analysis c2010 a149-610 v5923 a

In this chapter, we present a brief overview of current knowledge about the promoters of plant microRNAs (miRNAs), and provide a step-by-step guide for predicting plant miRNA promoter elements using known transcription factor binding motifs. The approach to promoter element prediction is based on a carefully constructed collection of Positional Weight Matrices (PWMs) for known transcription factors (TFs) in Arabidopsis. A key concept of the method is to use scoring thresholds for potential binding sites that are appropriate to each individual transcription factor. While the procedure can be applied to search for Transcription Factor Binding Sites (TFBSs) in any pol-II promoter region, it is particularly practical for the case of plant miRNA promoters where upstream sequence regions and binding sites are not readily available in existing databases. The majority of the material described in this chapter is available for download at http://microrna.gr.

[Link to Tools and Supplementary Materials]

10aMicroRNAs10aPromoter Regions, Genetic10aTranscription Factors1 aMegraw, Molly1 aHatzigeorgiou, Artemis, G uhttps://megraw.cgrb.oregonstate.edu/node/32502129nas 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/32602435nas a2200385 4500008004100000022001400041245005900055210005800114260001300172300001200185490000700197520139400204653001401598653002401612653001201636653001801648653001001666653001101676653001201687653000901699653001401708653002801722653001601750653001901766653004101785653002501826100002001851700001801871700002001889700002001909700001901929700003001948700002201978856004902000 2008 eng d a1362-496200aFrequency and fate of microRNA editing in human brain.0 aFrequency and fate of microRNA editing in human brain c2008 Sep a5270-800 v363 a

Primary transcripts of certain microRNA (miRNA) genes (pri-miRNAs) are subject to RNA editing that converts adenosine to inosine (A-->I RNA editing). However, the frequency of the pri-miRNA editing and the fate of edited pri-miRNAs remain largely to be determined. Examination of already known pri-miRNA editing sites indicated that adenosine residues of the UAG triplet sequence might be edited more frequently. In the present study, therefore, we conducted a large-scale survey of human pri-miRNAs containing the UAG triplet sequence. By direct sequencing of RT-PCR products corresponding to pri-miRNAs, we examined 209 pri-miRNAs and identified 43 UAG and also 43 non-UAG editing sites in 47 pri-miRNAs, which were highly edited in human brain. In vitro miRNA processing assay using recombinant Drosha-DGCR8 and Dicer-TRBP (the human immuno deficiency virus transactivating response RNA-binding protein) complexes revealed that a majority of pri-miRNA editing is likely to interfere with the miRNA processing steps. In addition, four new edited miRNAs with altered seed sequences were identified by targeted cloning and sequencing of the miRNAs that would be processed from edited pri-miRNAs. Our studies predict that approximately 16% of human pri-miRNAs are subject to A-->I editing and, thus, miRNA editing could have a large impact on the miRNA-mediated gene silencing.

10aAdenosine10aAdenosine Deaminase10aAnimals10aBase Sequence10aBrain10aHumans10aInosine10aMice10aMicroRNAs10aMolecular Sequence Data10aRNA Editing10aRNA Precursors10aRNA Processing, Post-Transcriptional10aRNA-Binding Proteins1 aKawahara, Yukio1 aMegraw, Molly1 aKreider, Edward1 aIizasa, Hisashi1 aValente, Louis1 aHatzigeorgiou, Artemis, G1 aNishikura, Kazuko uhttps://megraw.cgrb.oregonstate.edu/node/32703231nas a2200709 4500008004100000022001400041245010600055210006900161260001600230300001100246490000800257520120600265653001801471653002001489653002401509653002101533653001101554653003001565653004301595653001801638653001101656653001401667653002101681653002201702653002101724653001901745653002201764100001501786700002101801700001801822700002601840700001901866700001401885700002001899700002501919700002301944700002001967700002601987700002102013700001702034700001802051700001502069700001602084700001602100700002402116700001802140700002402158700002902182700002002211700002502231700002402256700002202280700001802302700001802320700002002338700002202358700002302380700003002403700002002433700001902453856004902472 2008 eng d a1091-649000aGenomic and epigenetic alterations deregulate microRNA expression in human epithelial ovarian cancer.0 aGenomic and epigenetic alterations deregulate microRNA expressio c2008 May 13 a7004-90 v1053 a

MicroRNAs (miRNAs) are an abundant class of small noncoding RNAs that function as negative gene regulators. miRNA deregulation is involved in the initiation and progression of human cancer; however, the underlying mechanism and its contributions to genome-wide transcriptional changes in cancer are still largely unknown. We studied miRNA deregulation in human epithelial ovarian cancer by integrative genomic approach, including miRNA microarray (n = 106), array-based comparative genomic hybridization (n = 109), cDNA microarray (n = 76), and tissue array (n = 504). miRNA expression is markedly down-regulated in malignant transformation and tumor progression. Genomic copy number loss and epigenetic silencing, respectively, may account for the down-regulation of approximately 15% and at least approximately 36% of miRNAs in advanced ovarian tumors and miRNA down-regulation contributes to a genome-wide transcriptional deregulation. Last, eight miRNAs located in the chromosome 14 miRNA cluster (Dlk1-Gtl2 domain) were identified as potential tumor suppressor genes. Therefore, our results suggest that miRNAs may offer new biomarkers and therapeutic targets in epithelial ovarian cancer.

10aDNA, Neoplasm10aDown-Regulation10aEpigenesis, Genetic10aEpithelial Cells10aFemale10aGene Expression Profiling10aGene Expression Regulation, Neoplastic10aGenome, Human10aHumans10aMicroRNAs10aNeoplasm Staging10aOvarian Neoplasms10aRibonuclease III10aRNA, Messenger10aSurvival Analysis1 aZhang, Lin1 aVolinia, Stefano1 aBonome, Tomas1 aCalin, George, Adrian1 aGreshock, Joel1 aYang, Nuo1 aLiu, Chang-Gong1 aGiannakakis, Antonis1 aAlexiou, Pangiotis1 aHasegawa, Kosei1 aJohnstone, Cameron, N1 aMegraw, Molly, S1 aAdams, Sarah1 aLassus, Heini1 aHuang, Jia1 aKaur, Sippy1 aLiang, Shun1 aSethupathy, Praveen1 aLeminen, Arto1 aSimossis, Victor, A1 aSandaltzopoulos, Raphael1 aNaomoto, Yoshio1 aKatsaros, Dionyssios1 aGimotty, Phyllis, A1 aDeMichele, Angela1 aHuang, Qihong1 aBützow, Ralf1 aRustgi, Anil, K1 aWeber, Barbara, L1 aBirrer, Michael, J1 aHatzigeorgiou, Artemis, G1 aCroce, Carlo, M1 aCoukos, George uhttps://megraw.cgrb.oregonstate.edu/node/32802199nas a2200301 4500008004100000022001400041245009100055210006900146260001300215300001200228490000700240520133700247653001201584653003701596653002801633653001301661653001101674653001301685653000901698653001401707653000901721653002801730100001801758700002401776700001801800700003001818856004901848 2007 eng d a1362-496200amiRGen: a database for the study of animal microRNA genomic organization and function.0 amiRGen a database for the study of animal microRNA genomic organ c2007 Jan aD149-550 v353 a

miRGen is an integrated database of (i) positional relationships between animal miRNAs and genomic annotation sets and (ii) animal miRNA targets according to combinations of widely used target prediction programs. A major goal of the database is the study of the relationship between miRNA genomic organization and miRNA function. This is made possible by three integrated and user friendly interfaces. The Genomics interface allows the user to explore where whole-genome collections of miRNAs are located with respect to UCSC genome browser annotation sets such as Known Genes, Refseq Genes, Genscan predicted genes, CpG islands and pseudogenes. These miRNAs are connected through the Targets interface to their experimentally supported target genes from TarBase, as well as computationally predicted target genes from optimized intersections and unions of several widely used mammalian target prediction programs. Finally, the Clusters interface provides predicted miRNA clusters at any given inter-miRNA distance and provides specific functional information on the targets of miRNAs within each cluster. All of these unique features of miRGen are designed to facilitate investigations into miRNA genomic organization, co-transcription and targeting. miRGen can be freely accessed at http://www.diana.pcbi.upenn.edu/miRGen.

10aAnimals10aData Interpretation, Statistical10aDatabases, Nucleic Acid10aGenomics10aHumans10aInternet10aMice10aMicroRNAs10aRats10aUser-Computer Interface1 aMegraw, Molly1 aSethupathy, Praveen1 aCorda, Benoit1 aHatzigeorgiou, Artemis, G uhttps://megraw.cgrb.oregonstate.edu/node/32901508nas a2200301 4500008004100000022001400041245010700055210006900162260001300231300001000244490000600254520059300260653002800853653002800881653001200909653002600921653001900947653001100966653001400977653003000991653001901021653003201040653001301072100002401085700001801109700003001127856004901157 2006 eng d a1548-709100aA guide through present computational approaches for the identification of mammalian microRNA targets.0 aguide through present computational approaches for the identific c2006 Nov a881-60 v33 a

Computational microRNA (miRNA) target prediction is a field in flux. Here we present a guide through five widely used mammalian target prediction programs. We include an analysis of the performance of these individual programs and of various combinations of these programs. For this analysis we compiled several benchmark data sets of experimentally supported miRNA-target gene interactions. Based on the results, we provide a discussion on the status of target prediction and also suggest a stepwise approach toward predicting and selecting miRNA targets for experimental testing.

10a3' Untranslated Regions10a5' Untranslated Regions10aAnimals10aComputational Biology10aGene Targeting10aHumans10aMicroRNAs10aPredictive Value of Tests10aRNA, Messenger10aSensitivity and Specificity10aSoftware1 aSethupathy, Praveen1 aMegraw, Molly1 aHatzigeorgiou, Artemis, G uhttps://megraw.cgrb.oregonstate.edu/node/33001854nas a2200337 4500008004100000022001400041245005600055210005500111260001300166300001100179490000700190520089800197653001601095653001801111653001801129653002301147653002801170653001701198653001401215653003001229653001301259653002601272653003401298100001801332700001901350700002401369700002101393700002301414700003001437856004901467 2006 eng d a1355-838200aMicroRNA promoter element discovery in Arabidopsis.0 aMicroRNA promoter element discovery in Arabidopsis c2006 Sep a1612-90 v123 a

In this study we present a method of identifying Arabidopsis miRNA promoter elements using known transcription factor binding motifs. We provide a comparative analysis of the representation of these elements in miRNA promoters, protein-coding gene promoters, and random genomic sequences. We report five transcription factor (TF) binding motifs that show evidence of overrepresentation in miRNA promoter regions relative to the promoter regions of protein-coding genes. This investigation is based on the analysis of 800-nucleotide regions upstream of 63 experimentally verified Transcription Start Sites (TSS) for miRNA primary transcripts in Arabidopsis. While the TATA-box binding motif was also previously reported by Xie and colleagues, the transcription factors AtMYC2, ARF, SORLREP3, and LFY are identified for the first time as overrepresented binding motifs in miRNA promoters.

10aArabidopsis10aBase Sequence10aBinding Sites10aDatabases, Genetic10aFeedback, Physiological10aGenes, Plant10aMicroRNAs10aPromoter Regions, Genetic10aTATA Box10aTranscription Factors10aTranscription Initiation Site1 aMegraw, Molly1 aBaev, Vesselin1 aRusinov, Ventsislav1 aJensen, Shane, T1 aKalantidis, Kriton1 aHatzigeorgiou, Artemis, G uhttps://megraw.cgrb.oregonstate.edu/node/33102695nas a2200481 4500008004100000022001400041245007400055210006900129260001600198300001200214490000800226520132400234653002101558653001101579653001601590653003001606653001101636653001401647653001401661653003101675653004401706653002201750653002401772100001501796700001501811700001401826700001901840700002101859700002501880700001601905700002001921700002201941700002201963700001601985700002102001700002502022700002502047700002702072700002402099700002202123700001902145856004902164 2006 eng d a0027-842400amicroRNAs exhibit high frequency genomic alterations in human cancer.0 amicroRNAs exhibit high frequency genomic alterations in human ca c2006 Jun 13 a9136-410 v1033 a

MicroRNAs (miRNAs) are endogenous noncoding RNAs, which negatively regulate gene expression. To determine genomewide miRNA DNA copy number abnormalities in cancer, 283 known human miRNA genes were analyzed by high-resolution array-based comparative genomic hybridization in 227 human ovarian cancer, breast cancer, and melanoma specimens. A high proportion of genomic loci containing miRNA genes exhibited DNA copy number alterations in ovarian cancer (37.1%), breast cancer (72.8%), and melanoma (85.9%), where copy number alterations observed in >15% tumors were considered significant for each miRNA gene. We identified 41 miRNA genes with gene copy number changes that were shared among the three cancer types (26 with gains and 15 with losses) as well as miRNA genes with copy number changes that were unique to each tumor type. Importantly, we show that miRNA copy changes correlate with miRNA expression. Finally, we identified high frequency copy number abnormalities of Dicer1, Argonaute2, and other miRNA-associated genes in breast and ovarian cancer as well as melanoma. These findings support the notion that copy number alterations of miRNAs and their regulatory genes are highly prevalent in cancer and may account partly for the frequent miRNA gene deregulation reported in several tumor types.

10aBreast Neoplasms10aFemale10aGene Dosage10aGene Expression Profiling10aHumans10aMicroRNAs10aNeoplasms10aNucleic Acid Hybridization10aOligonucleotide Array Sequence Analysis10aOvarian Neoplasms10aStatistics as Topic1 aZhang, Lin1 aHuang, Jia1 aYang, Nuo1 aGreshock, Joel1 aMegraw, Molly, S1 aGiannakakis, Antonis1 aLiang, Shun1 aNaylor, Tara, L1 aBarchetti, Andrea1 aWard, Michelle, R1 aYao, George1 aMedina, Angelica1 aO'brien-Jenkins, Ann1 aKatsaros, Dionyssios1 aHatzigeorgiou, Artemis1 aGimotty, Phyllis, A1 aWeber, Barbara, L1 aCoukos, George uhttps://megraw.cgrb.oregonstate.edu/node/332