TY - JOUR T1 - Metabolomics analysis reveals both plant variety and choice of hormone treatment modulate vinca alkaloid production in Catharanthus roseus JF - Plant Direct Y1 - 2020 A1 - Valerie N. Fraser A1 - Benjamin Philmus A1 - Molly Megraw AB -

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.

VL - 4 UR - https://onlinelibrary.wiley.com/doi/10.1002/pld3.267 IS - 9 ER - TY - JOUR T1 - MicroRNA promoter analysis. JF - Methods Mol Biol Y1 - 2010 A1 - Megraw, Molly A1 - Hatzigeorgiou, Artemis G KW - MicroRNAs KW - Promoter Regions, Genetic KW - Transcription Factors AB -

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]

VL - 592 ER - TY - JOUR T1 - miRGen 2.0: a database of microRNA genomic information and regulation. JF - Nucleic Acids Res Y1 - 2010 A1 - Alexiou, Panagiotis A1 - Vergoulis, Thanasis A1 - Gleditzsch, Martin A1 - Prekas, George A1 - Dalamagas, Theodore A1 - Megraw, Molly A1 - Grosse, Ivo A1 - Sellis, Timos A1 - Hatzigeorgiou, Artemis G KW - 3' Untranslated Regions KW - Algorithms KW - Animals KW - Cell Line, Tumor KW - Computational Biology KW - Databases, Genetic KW - Databases, Nucleic Acid KW - Humans KW - Information Storage and Retrieval KW - Internet KW - Mice KW - MicroRNAs KW - Polymorphism, Single Nucleotide KW - Software KW - Transcription Factors AB -

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/.

VL - 38 IS - Database issue ER - TY - JOUR T1 - miRGen: a database for the study of animal microRNA genomic organization and function. JF - Nucleic Acids Res Y1 - 2007 A1 - Megraw, Molly A1 - Sethupathy, Praveen A1 - Corda, Benoit A1 - Hatzigeorgiou, Artemis G KW - Animals KW - Data Interpretation, Statistical KW - Databases, Nucleic Acid KW - Genomics KW - Humans KW - Internet KW - Mice KW - MicroRNAs KW - Rats KW - User-Computer Interface AB -

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.

VL - 35 IS - Database issue ER - TY - JOUR T1 - MicroRNA promoter element discovery in Arabidopsis. JF - RNA Y1 - 2006 A1 - Megraw, Molly A1 - Baev, Vesselin A1 - Rusinov, Ventsislav A1 - Jensen, Shane T A1 - Kalantidis, Kriton A1 - Hatzigeorgiou, Artemis G KW - Arabidopsis KW - Base Sequence KW - Binding Sites KW - Databases, Genetic KW - Feedback, Physiological KW - Genes, Plant KW - MicroRNAs KW - Promoter Regions, Genetic KW - TATA Box KW - Transcription Factors KW - Transcription Initiation Site AB -

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.

VL - 12 IS - 9 ER - TY - JOUR T1 - microRNAs exhibit high frequency genomic alterations in human cancer. JF - Proc Natl Acad Sci U S A Y1 - 2006 A1 - Zhang, Lin A1 - Huang, Jia A1 - Yang, Nuo A1 - Greshock, Joel A1 - Megraw, Molly S A1 - Giannakakis, Antonis A1 - Liang, Shun A1 - Naylor, Tara L A1 - Barchetti, Andrea A1 - Ward, Michelle R A1 - Yao, George A1 - Medina, Angelica A1 - O'brien-Jenkins, Ann A1 - Katsaros, Dionyssios A1 - Hatzigeorgiou, Artemis A1 - Gimotty, Phyllis A A1 - Weber, Barbara L A1 - Coukos, George KW - Breast Neoplasms KW - Female KW - Gene Dosage KW - Gene Expression Profiling KW - Humans KW - MicroRNAs KW - Neoplasms KW - Nucleic Acid Hybridization KW - Oligonucleotide Array Sequence Analysis KW - Ovarian Neoplasms KW - Statistics as Topic AB -

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.

VL - 103 IS - 24 ER -