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/pld3.26701594nas 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/32402199nas 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/32901854nas 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