<?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%">Valerie N. Fraser</style></author><author><style face="normal" font="default" size="100%">Benjamin Philmus</style></author><author><style face="normal" font="default" size="100%">Molly Megraw</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Metabolomics analysis reveals both plant variety and choice of hormone treatment modulate vinca alkaloid production in Catharanthus roseus</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%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2020</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://onlinelibrary.wiley.com/doi/10.1002/pld3.267</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">4</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;span style=&quot;color: rgb(28, 29, 30); font-family: &amp;quot;Open Sans&amp;quot;, icomoon, sans-serif; font-size: 16px;&quot;&gt;The medicinal plant&amp;nbsp;&lt;/span&gt;&lt;i style=&quot;box-sizing: border-box; color: rgb(28, 29, 30); font-family: &amp;quot;Open Sans&amp;quot;, icomoon, sans-serif; font-size: 16px;&quot;&gt;Catharanthus roseus&lt;/i&gt;&lt;span style=&quot;color: rgb(28, 29, 30); font-family: &amp;quot;Open Sans&amp;quot;, icomoon, sans-serif; font-size: 16px;&quot;&gt;&amp;nbsp;produces numerous secondary metabolites of interest for the treatment of many diseases &amp;ndash; most notably for the terpene indole alkaloid (TIA) vinblastine, which is used in the treatment of leukemia and Hodgkin&amp;#39;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&amp;nbsp;&lt;/span&gt;&lt;i style=&quot;box-sizing: border-box; color: rgb(28, 29, 30); font-family: &amp;quot;Open Sans&amp;quot;, icomoon, sans-serif; font-size: 16px;&quot;&gt;C. roseus&lt;/i&gt;&lt;span style=&quot;color: rgb(28, 29, 30); font-family: &amp;quot;Open Sans&amp;quot;, icomoon, sans-serif; font-size: 16px;&quot;&gt;. 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&amp;#39;omics resources in commonly used&amp;nbsp;&lt;/span&gt;&lt;i style=&quot;box-sizing: border-box; color: rgb(28, 29, 30); font-family: &amp;quot;Open Sans&amp;quot;, icomoon, sans-serif; font-size: 16px;&quot;&gt;C. roseus&lt;/i&gt;&lt;span style=&quot;color: rgb(28, 29, 30); font-family: &amp;quot;Open Sans&amp;quot;, icomoon, sans-serif; font-size: 16px;&quot;&gt;&amp;nbsp;varieties and the need for caution when extrapolating results from one cultivar to another.&lt;/span&gt;&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">9</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%">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%">Sergei A Filichkin</style></author><author><style face="normal" font="default" size="100%">Mitra Ansariola</style></author><author><style face="normal" font="default" size="100%">Valerie N Fraser</style></author><author><style face="normal" font="default" size="100%">Molly Megraw</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Identification of transcription factors from NF-Y, NAC, and SPL families responding to osmotic stress in multiple tomato varieties</style></title><secondary-title><style face="normal" font="default" size="100%">Plant Science</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2018</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.sciencedirect.com/science/article/abs/pii/S0168945218303534</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">274</style></volume><pages><style face="normal" font="default" size="100%">441-450</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&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%">Mitra Ansariola</style></author><author><style face="normal" font="default" size="100%">Molly Megraw</style></author><author><style face="normal" font="default" size="100%">David Koslicki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">IndeCut evaluates performance of network motif discovery algorithms</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2018</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://academic.oup.com/bioinformatics/article/34/9/1514/4721785</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">34</style></volume><pages><style face="normal" font="default" size="100%">1514-1521</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;div&gt;Motivation&lt;/div&gt;&lt;div&gt;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&amp;mdash;thus it was not possible to assess the validity of resulting network motifs.&lt;/div&gt;&lt;div&gt;&amp;nbsp;&lt;/div&gt;&lt;div&gt;Results&lt;/div&gt;&lt;div&gt;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.&lt;/div&gt;</style></abstract><issue><style face="normal" font="default" size="100%">9</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%">Joanna Friesner</style></author><author><style face="normal" font="default" size="100%">Sarah M. Assmann</style></author><author><style face="normal" font="default" size="100%">Ruth Bastow</style></author><author><style face="normal" font="default" size="100%">Julia Bailey-Serres</style></author><author><style face="normal" font="default" size="100%">Jim Beynon</style></author><author><style face="normal" font="default" size="100%">Volker Brendel</style></author><author><style face="normal" font="default" size="100%">C. Robin Buell</style></author><author><style face="normal" font="default" size="100%">Alexander Bucksch</style></author><author><style face="normal" font="default" size="100%">Wolfgang Busch</style></author><author><style face="normal" font="default" size="100%">Taku Demura</style></author><author><style face="normal" font="default" size="100%">Jose R. Dinneny</style></author><author><style face="normal" font="default" size="100%">Colleen J. Doherty</style></author><author><style face="normal" font="default" size="100%">Andrea L. Eveland</style></author><author><style face="normal" font="default" size="100%">Pascal Falter-Braun</style></author><author><style face="normal" font="default" size="100%">Malia A. Gehan</style></author><author><style face="normal" font="default" size="100%">Michael Gonzales</style></author><author><style face="normal" font="default" size="100%">Erich Grotewold</style></author><author><style face="normal" font="default" size="100%">Rodrigo Gutierrez</style></author><author><style face="normal" font="default" size="100%">Ute Kramer</style></author><author><style face="normal" font="default" size="100%">Gabriel Krouk</style></author><author><style face="normal" font="default" size="100%">Shisong Ma</style></author><author><style face="normal" font="default" size="100%">R.J. Cody Markelz</style></author><author><style face="normal" font="default" size="100%">Molly Megraw</style></author><author><style face="normal" font="default" size="100%">Blake C. Meyers</style></author><author><style face="normal" font="default" size="100%">James A.H. Murray</style></author><author><style face="normal" font="default" size="100%">Nicholas J. Provart</style></author><author><style face="normal" font="default" size="100%">Sue Rhee</style></author><author><style face="normal" font="default" size="100%">Roger Smith</style></author><author><style face="normal" font="default" size="100%">Edgar P. Spalding</style></author><author><style face="normal" font="default" size="100%">Crispin Taylor</style></author><author><style face="normal" font="default" size="100%">Tracy K. Teal</style></author><author><style face="normal" font="default" size="100%">Keiko U. Torii</style></author><author><style face="normal" font="default" size="100%">Chris Town</style></author><author><style face="normal" font="default" size="100%">Matthew Vaughn</style></author><author><style face="normal" font="default" size="100%">Richard Vierstra</style></author><author><style face="normal" font="default" size="100%">Doreen Ware</style></author><author><style face="normal" font="default" size="100%">Olivia Wilkins</style></author><author><style face="normal" font="default" size="100%">Cranos Williams</style></author><author><style face="normal" font="default" size="100%">Siobhan M. Brady</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The Next Generation of Training for Arabidopsis Researchers: Bioinformatics and Quantitative Biology</style></title><secondary-title><style face="normal" font="default" size="100%">Plant Physiology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2017</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.plantphysiol.org/content/175/4/1499</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">175</style></volume><pages><style face="normal" font="default" size="100%">1499-1509</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;div&gt;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.&lt;/div&gt;</style></abstract></record></records></xml>