<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Colleen Doherty</style></author><author><style face="normal" font="default" size="100%">Joanna Friesner</style></author><author><style face="normal" font="default" size="100%">Brian Gregory</style></author><author><style face="normal" font="default" size="100%">Ann Loraine</style></author><author><style face="normal" font="default" size="100%">Molly Megraw</style></author><author><style face="normal" font="default" size="100%">Nicholas Provart</style></author><author><style face="normal" font="default" size="100%">R Keith Slotkin</style></author><author><style face="normal" font="default" size="100%">Chris Town</style></author><author><style face="normal" font="default" size="100%">Sarah M Assmann</style></author><author><style face="normal" font="default" size="100%">Michael Axtell</style></author><author><style face="normal" font="default" size="100%">Tanya Berardini</style></author><author><style face="normal" font="default" size="100%">Sixue Chen</style></author><author><style face="normal" font="default" size="100%">Malia Gehan</style></author><author><style face="normal" font="default" size="100%">Eva Huala</style></author><author><style face="normal" font="default" size="100%">Pankaj Jaiswal</style></author><author><style face="normal" font="default" size="100%">Stephen Larson</style></author><author><style face="normal" font="default" size="100%">Song Li</style></author><author><style face="normal" font="default" size="100%">Sean May</style></author><author><style face="normal" font="default" size="100%">Todd Michael</style></author><author><style face="normal" font="default" size="100%">Chris Pires</style></author><author><style face="normal" font="default" size="100%">Chris Topp</style></author><author><style face="normal" font="default" size="100%">Justin Walley</style></author><author><style face="normal" font="default" size="100%">Eve Wurtele</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Arabidopsis bioinformatics resources: The current state, challenges, and priorities for the future</style></title><secondary-title><style face="normal" font="default" size="100%">Plant Direct</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">01/2019</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://onlinelibrary.wiley.com/doi/full/10.1002/pld3.109</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">3</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Filichkin, Sergei A</style></author><author><style face="normal" font="default" size="100%">Cumbie, Jason S</style></author><author><style face="normal" font="default" size="100%">Dharmawardhana, Palitha</style></author><author><style face="normal" font="default" size="100%">Jaiswal, Pankaj</style></author><author><style face="normal" font="default" size="100%">Chang, Jeff H</style></author><author><style face="normal" font="default" size="100%">Palusa, Saiprasad G</style></author><author><style face="normal" font="default" size="100%">Reddy, A S N</style></author><author><style face="normal" font="default" size="100%">Megraw, Molly</style></author><author><style face="normal" font="default" size="100%">Mockler, Todd C</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Environmental stresses modulate abundance and timing of alternatively spliced circadian transcripts in Arabidopsis.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol Plant</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Mol Plant</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Alternative Splicing</style></keyword><keyword><style  face="normal" font="default" size="100%">Arabidopsis</style></keyword><keyword><style  face="normal" font="default" size="100%">Arabidopsis Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Circadian Clocks</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Plant</style></keyword><keyword><style  face="normal" font="default" size="100%">Introns</style></keyword><keyword><style  face="normal" font="default" size="100%">Nonsense Mediated mRNA Decay</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2015 Feb</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">207-27</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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&amp;nbsp;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.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Filichkin, Sergei A</style></author><author><style face="normal" font="default" size="100%">Cumbie, Jason S</style></author><author><style face="normal" font="default" size="100%">Dharmawadhana, J Palitha</style></author><author><style face="normal" font="default" size="100%">Jaiswal, Pankaj</style></author><author><style face="normal" font="default" size="100%">Chang, Jeff H</style></author><author><style face="normal" font="default" size="100%">Palusa, Saiprasad G</style></author><author><style face="normal" font="default" size="100%">Reddy, A S N</style></author><author><style face="normal" font="default" size="100%">Megraw, Molly</style></author><author><style face="normal" font="default" size="100%">Mockler, Todd C</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Environmental Stresses Modulate Abundance and Timing of Alternatively Spliced Circadian Transcripts in Arabidopsis.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol Plant</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Mol Plant</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2014 Nov 3</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Brady, Siobhan M</style></author><author><style face="normal" font="default" size="100%">Zhang, Lifang</style></author><author><style face="normal" font="default" size="100%">Megraw, Molly</style></author><author><style face="normal" font="default" size="100%">Martinez, Natalia J</style></author><author><style face="normal" font="default" size="100%">Jiang, Eric</style></author><author><style face="normal" font="default" size="100%">Yi, Charles S</style></author><author><style face="normal" font="default" size="100%">Liu, Weilin</style></author><author><style face="normal" font="default" size="100%">Zeng, Anna</style></author><author><style face="normal" font="default" size="100%">Taylor-Teeples, Mallorie</style></author><author><style face="normal" font="default" size="100%">Kim, Dahae</style></author><author><style face="normal" font="default" size="100%">Ahnert, Sebastian</style></author><author><style face="normal" font="default" size="100%">Ohler, Uwe</style></author><author><style face="normal" font="default" size="100%">Ware, Doreen</style></author><author><style face="normal" font="default" size="100%">Walhout, Albertha J M</style></author><author><style face="normal" font="default" size="100%">Benfey, Philip N</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A stele-enriched gene regulatory network in the Arabidopsis root.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol Syst Biol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Mol. Syst. Biol.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Arabidopsis</style></keyword><keyword><style  face="normal" font="default" size="100%">Arabidopsis Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Regulatory Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">MicroRNAs</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Roots</style></keyword><keyword><style  face="normal" font="default" size="100%">Reproducibility of Results</style></keyword><keyword><style  face="normal" font="default" size="100%">Systems Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Two-Hybrid System Techniques</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011 Jan 18</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">7</style></volume><pages><style face="normal" font="default" size="100%">459</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Megraw, Molly</style></author><author><style face="normal" font="default" size="100%">Pereira, Fernando</style></author><author><style face="normal" font="default" size="100%">Jensen, Shane T</style></author><author><style face="normal" font="default" size="100%">Ohler, Uwe</style></author><author><style face="normal" font="default" size="100%">Hatzigeorgiou, Artemis G</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A transcription factor affinity-based code for mammalian transcription initiation.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Res</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Genome Res.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Base Composition</style></keyword><keyword><style  face="normal" font="default" size="100%">Databases, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Promoter Regions, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA Polymerase II</style></keyword><keyword><style  face="normal" font="default" size="100%">TATA Box</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription Initiation Site</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription, Genetic</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2009 Apr</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">19</style></volume><pages><style face="normal" font="default" size="100%">644-56</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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&amp;#39;-ends. Using this high-resolution single-peak model, we predict TSS for approximately 70% of mammalian microRNAs based on currently available data.&lt;/p&gt;&lt;p&gt;&lt;a href=&quot;http://megraw-dev.cgrb.oregonstate.edu/node/715&quot;&gt;[Links to Tools and Supplementary Materials]&lt;/a&gt;&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhang, Lin</style></author><author><style face="normal" font="default" size="100%">Volinia, Stefano</style></author><author><style face="normal" font="default" size="100%">Bonome, Tomas</style></author><author><style face="normal" font="default" size="100%">Calin, George Adrian</style></author><author><style face="normal" font="default" size="100%">Greshock, Joel</style></author><author><style face="normal" font="default" size="100%">Yang, Nuo</style></author><author><style face="normal" font="default" size="100%">Liu, Chang-Gong</style></author><author><style face="normal" font="default" size="100%">Giannakakis, Antonis</style></author><author><style face="normal" font="default" size="100%">Alexiou, Pangiotis</style></author><author><style face="normal" font="default" size="100%">Hasegawa, Kosei</style></author><author><style face="normal" font="default" size="100%">Johnstone, Cameron N</style></author><author><style face="normal" font="default" size="100%">Megraw, Molly S</style></author><author><style face="normal" font="default" size="100%">Adams, Sarah</style></author><author><style face="normal" font="default" size="100%">Lassus, Heini</style></author><author><style face="normal" font="default" size="100%">Huang, Jia</style></author><author><style face="normal" font="default" size="100%">Kaur, Sippy</style></author><author><style face="normal" font="default" size="100%">Liang, Shun</style></author><author><style face="normal" font="default" size="100%">Sethupathy, Praveen</style></author><author><style face="normal" font="default" size="100%">Leminen, Arto</style></author><author><style face="normal" font="default" size="100%">Simossis, Victor A</style></author><author><style face="normal" font="default" size="100%">Sandaltzopoulos, Raphael</style></author><author><style face="normal" font="default" size="100%">Naomoto, Yoshio</style></author><author><style face="normal" font="default" size="100%">Katsaros, Dionyssios</style></author><author><style face="normal" font="default" size="100%">Gimotty, Phyllis A</style></author><author><style face="normal" font="default" size="100%">DeMichele, Angela</style></author><author><style face="normal" font="default" size="100%">Huang, Qihong</style></author><author><style face="normal" font="default" size="100%">Bützow, Ralf</style></author><author><style face="normal" font="default" size="100%">Rustgi, Anil K</style></author><author><style face="normal" font="default" size="100%">Weber, Barbara L</style></author><author><style face="normal" font="default" size="100%">Birrer, Michael J</style></author><author><style face="normal" font="default" size="100%">Hatzigeorgiou, Artemis G</style></author><author><style face="normal" font="default" size="100%">Croce, Carlo M</style></author><author><style face="normal" font="default" size="100%">Coukos, George</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genomic and epigenetic alterations deregulate microRNA expression in human epithelial ovarian cancer.</style></title><secondary-title><style face="normal" font="default" size="100%">Proc Natl Acad Sci U S A</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Proc. Natl. Acad. Sci. U.S.A.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">DNA, Neoplasm</style></keyword><keyword><style  face="normal" font="default" size="100%">Down-Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Epigenesis, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Epithelial Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Neoplastic</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">MicroRNAs</style></keyword><keyword><style  face="normal" font="default" size="100%">Neoplasm Staging</style></keyword><keyword><style  face="normal" font="default" size="100%">Ovarian Neoplasms</style></keyword><keyword><style  face="normal" font="default" size="100%">Ribonuclease III</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Messenger</style></keyword><keyword><style  face="normal" font="default" size="100%">Survival Analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2008 May 13</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">105</style></volume><pages><style face="normal" font="default" size="100%">7004-9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">19</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Megraw, Molly</style></author><author><style face="normal" font="default" size="100%">Baev, Vesselin</style></author><author><style face="normal" font="default" size="100%">Rusinov, Ventsislav</style></author><author><style face="normal" font="default" size="100%">Jensen, Shane T</style></author><author><style face="normal" font="default" size="100%">Kalantidis, Kriton</style></author><author><style face="normal" font="default" size="100%">Hatzigeorgiou, Artemis G</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">MicroRNA promoter element discovery in Arabidopsis.</style></title><secondary-title><style face="normal" font="default" size="100%">RNA</style></secondary-title><alt-title><style face="normal" font="default" size="100%">RNA</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Arabidopsis</style></keyword><keyword><style  face="normal" font="default" size="100%">Base Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Binding Sites</style></keyword><keyword><style  face="normal" font="default" size="100%">Databases, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Feedback, Physiological</style></keyword><keyword><style  face="normal" font="default" size="100%">Genes, Plant</style></keyword><keyword><style  face="normal" font="default" size="100%">MicroRNAs</style></keyword><keyword><style  face="normal" font="default" size="100%">Promoter Regions, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">TATA Box</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcription Initiation Site</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2006 Sep</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">1612-9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">9</style></issue></record></records></xml>