40 results on '"Anthon, Christian"'
Search Results
2. Massively targeted evaluation of therapeutic CRISPR off-targets in cells
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Pan, Xiaoguang, Qu, Kunli, Yuan, Hao, Xiang, Xi, Anthon, Christian, Pashkova, Liubov, Liang, Xue, Han, Peng, Corsi, Giulia I., Xu, Fengping, Liu, Ping, Zhong, Jiayan, Zhou, Yan, Ma, Tao, Jiang, Hui, Liu, Junnian, Wang, Jian, Jessen, Niels, Bolund, Lars, Yang, Huanming, Xu, Xun, Church, George M., Gorodkin, Jan, Lin, Lin, and Luo, Yonglun
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- 2022
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3. Enhancing CRISPR-Cas9 gRNA efficiency prediction by data integration and deep learning
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Xiang, Xi, Corsi, Giulia I., Anthon, Christian, Qu, Kunli, Pan, Xiaoguang, Liang, Xue, Han, Peng, Dong, Zhanying, Liu, Lijun, Zhong, Jiayan, Ma, Tao, Wang, Jinbao, Zhang, Xiuqing, Jiang, Hui, Xu, Fengping, Liu, Xin, Xu, Xun, Wang, Jian, Yang, Huanming, Bolund, Lars, Church, George M., Lin, Lin, Gorodkin, Jan, and Luo, Yonglun
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- 2021
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4. Novel circRNA discovery in sheep shows evidence of high backsplice junction conservation
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Varela-Martínez, Endika, Corsi, Giulia I., Anthon, Christian, Gorodkin, Jan, and Jugo, Begoña M.
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- 2021
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5. CRISPRi screen for enhancing heterologous α-amylase yield in Bacillus subtilis.
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Geissler, Adrian Sven, Fehler, Annaleigh Ohrt, Poulsen, Line Dahl, González-Tortuero, Enrique, Kallehauge, Thomas Beuchert, Alkan, Ferhat, Anthon, Christian, Seemann, Stefan Ernst, Rasmussen, Michael Dolberg, Breüner, Anne, Hjort, Carsten, Vinther, Jeppe, and Gorodkin, Jan
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CRISPRS ,BACILLUS subtilis ,AMYLASES ,GENE expression ,CYTOCHROME oxidase ,ANTISENSE RNA ,OPERONS - Abstract
Yield improvements in cell factories can potentially be obtained by fine-tuning the regulatory mechanisms for gene candidates. In pursuit of such candidates, we performed RNA-sequencing of two α-amylase producing Bacillus strains and predict hundreds of putative novel non-coding transcribed regions. Surprisingly, we found among hundreds of non-coding and structured RNA candidates that non-coding genomic regions are proportionally undergoing the highest changes in expression during fermentation. Since these classes of RNA are also understudied, we targeted the corresponding genomic regions with CRIPSRi knockdown to test for any potential impact on the yield. From differentially expression analysis, we selected 53 non-coding candidates. Although CRISPRi knockdowns target both the sense and the antisense strand, the CRISPRi experiment cannot link causes for yield changes to the sense or antisense disruption. Nevertheless, we observed on several instances with strong changes in enzyme yield. The knockdown targeting the genomic region for a putative antisense RNA of the 3′ UTR of the skfA-skfH operon led to a 21% increase in yield. In contrast, the knockdown targeting the genomic regions of putative antisense RNAs of the cytochrome c oxidase subunit 1 (ctaD) , the sigma factor sigH , and the uncharacterized gene yhfT decreased yields by 31 to 43%. [ABSTRACT FROM AUTHOR]
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- 2023
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6. Letter to the editor: Testing on external independent datasets is necessary to corroborate machine learning model improvement.
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Corsi, Giulia Ilaria, Anthon, Christian, and Gorodkin, Jan
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MACHINE learning , *DEEP learning , *SUPERVISED learning , *GENOME editing - Abstract
Different TL techniques were meticulously tested using the surrogate-based dataset of Wang et al. as the "source" dataset for pre-training and one of the 10 smaller endogenous or functional knockout datasets as the "target" for refining the TL model. It is also worth noticing that CRISPRon outperforms the DeepCRISTL model trained on the dataset of Chari I et al. i on seven of the test datasets (Fig. The genome engineering revolution of the past decade has been fueled by the development of several computational tools for the design of experiments mediated by the CRISPR/Cas9 endonuclease ([3]). [Extracted from the article]
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- 2023
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7. The impact of PrsA over-expression on the Bacillus subtilis transcriptome during fed-batch fermentation of alpha-amylase production.
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Geissler, Adrian S., Poulsen, Line D., Doncheva, Nadezhda T., Anthon, Christian, Seemann, Stefan E., González-Tortuero, Enrique, Breüner, Anne, Jensen, Lars J., Hjort, Carsten, Vinther, Jeppe, and Gorodkin, Jan
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AMYLASES ,BACILLUS subtilis ,ALPHA-amylase ,AMINO acid metabolism ,PROTEIN folding ,FERMENTATION - Abstract
The production of the alpha-amylase (AMY) enzyme in Bacillus subtilis at a high rate leads to the accumulation of unfolded AMY, which causes secretion stress. The over-expression of the PrsA chaperone aids enzyme folding and reduces stress. To identify affected pathways and potential mechanisms involved in the reduced growth, we analyzed the transcriptomic differences during fed-batch fermentation between a PrsA over-expressing strain and control in a time-series RNA-seq experiment. We observe transcription in 542 unannotated regions, of which 234 had significant changes in expression levels between the samples. Moreover, 1,791 protein-coding sequences, 80 non-coding genes, and 20 riboswitches overlapping UTR regions of coding genes had significant changes in expression. We identified putatively regulated biological processes via gene-set over-representation analysis of the differentially expressed genes; overall, the analysis suggests that the PrsA over-expression affects ATP biosynthesis activity, amino acid metabolism, and cell wall stability. The investigation of the protein interaction network points to a potential impact on cell motility signaling. We discuss the impact of these highlighted mechanisms for reducing secretion stress or detrimental aspects of PrsA over-expression during AMY production. [ABSTRACT FROM AUTHOR]
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- 2022
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8. Kohn-Sham DFT results projected on ligand-field models: Using DFT to supplement ligand-field descriptions and to supply ligand-field parameters
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Schäffer, Claus E., Anthon, Christian, and Bendix, Jesper
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- 2009
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9. Analyses of pig genomes provide insight into porcine demography and evolution
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Groenen, Martien A. M., Archibald, Alan L., Uenishi, Hirohide, Tuggle, Christopher K., Takeuchi, Yasuhiro, Rothschild, Max F., Rogel-Gaillard, Claire, Park, Chankyu, Milan, Denis, Megens, Hendrik-Jan, Li, Shengting, Larkin, Denis M., Kim, Heebal, Frantz, Laurent A. F., Caccamo, Mario, Ahn, Hyeonju, Aken, Bronwen L., Anselmo, Anna, Anthon, Christian, Auvil, Loretta, Badaoui, Bouabid, Beattie, Craig W., Bendixen, Christian, Berman, Daniel, Blecha, Frank, Blomberg, Jonas, Bolund, Lars, Bosse, Mirte, Botti, Sara, Bujie, Zhan, Bystrom, Megan, Capitanu, Boris, Carvalho-Silva, Denise, Chardon, Patrick, Chen, Celine, Cheng, Ryan, Choi, Sang-Haeng, Chow, William, Clark, Richard C., Clee, Christopher, Crooijmans, Richard P. M. A., Dawson, Harry D., Dehais, Patrice, De Sapio, Fioravante, Dibbits, Bert, Drou, Nizar, Du, Zhi-Qiang, Eversole, Kellye, Fadista, João, Fairley, Susan, Faraut, Thomas, Faulkner, Geoffrey J., Fowler, Katie E., Fredholm, Merete, Fritz, Eric, Gilbert, James G. R., Giuffra, Elisabetta, Gorodkin, Jan, Griffin, Darren K., Harrow, Jennifer L., Hayward, Alexander, Howe, Kerstin, Hu, Zhi-Liang, Humphray, Sean J., Hunt, Toby, Hornshøj, Henrik, Jeon, Jin-Tae, Jern, Patric, Jones, Matthew, Jurka, Jerzy, Kanamori, Hiroyuki, Kapetanovic, Ronan, Kim, Jaebum, Kim, Jae-Hwan, Kim, Kyu-Won, Kim, Tae-Hun, Larson, Greger, Lee, Kyooyeol, Lee, Kyung-Tai, Leggett, Richard, Lewin, Harris A., Li, Yingrui, Liu, Wansheng, Loveland, Jane E., Lu, Yao, Lunney, Joan K., Ma, Jian, Madsen, Ole, Mann, Katherine, Matthews, Lucy, McLaren, Stuart, Morozumi, Takeya, Murtaugh, Michael P., Narayan, Jitendra, Truong Nguyen, Dinh, Ni, Peixiang, Oh, Song-Jung, Onteru, Suneel, Panitz, Frank, Park, Eung-Woo, Park, Hong-Seog, Pascal, Geraldine, Paudel, Yogesh, Perez-Enciso, Miguel, Ramirez-Gonzalez, Ricardo, Reecy, James M., Rodriguez-Zas, Sandra, Rohrer, Gary A., Rund, Lauretta, Sang, Yongming, Schachtschneider, Kyle, Schraiber, Joshua G., Schwartz, John, Scobie, Linda, Scott, Carol, Searle, Stephen, Servin, Bertrand, Southey, Bruce R., Sperber, Goran, Stadler, Peter, Sweedler, Jonathan V., Tafer, Hakim, Thomsen, Bo, Wali, Rashmi, Wang, Jian, Wang, Jun, White, Simon, Xu, Xun, Yerle, Martine, Zhang, Guojie, Zhang, Jianguo, Zhang, Jie, Zhao, Shuhong, Rogers, Jane, Churcher, Carol, and Schook, Lawrence B.
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- 2012
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10. CRISPRon/off: CRISPR/Cas9 on- and off-target gRNA design.
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Anthon, Christian, Corsi, Giulia Ilaria, and Gorodkin, Jan
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INTERNET servers , *CRISPRS , *GENOME editing , *RNA - Abstract
Summary The effectiveness of CRISPR/Cas9-mediated genome editing experiments largely depends on the guide RNA (gRNA) used by the CRISPR/Cas9 system for target recognition and cleavage activation. Careful design is necessary to select a gRNA with high editing efficiency at the on-target site and with minimum off-target potential. Here, we present our webserver for gRNA design with a user-friendly graphical interface, which provides interoperability between our on- and off-target prediction tools, CRISPRon and CRISPRoff, for a complete and streamlined gRNA selection. Availability and implementation The graphical interface uses the Integrative Genomic Viewer (IGV) JavaScript plugin. The backend tools are implemented in Python and C. The CRISPRon and CRISPRoff webservers and command-line tools are freely available at https://rth.dk/resources/crispr. [ABSTRACT FROM AUTHOR]
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- 2022
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11. Mimicking the two-dimensional spectrochemical series using density functional computations
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Anthon, Christian, Bendix, Jesper, and Schaffer, Claus E.
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Stereochemistry -- Research ,Ligands -- Research ,Density functionals -- Usage ,Chemistry - Abstract
The study illustrated how Kohn-Sham density functional theory (KS-DFT) could be utilized to provide a computational supplement, when experimental ligand-field results are unobtainable.
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- 2004
12. Profiling microRNAs in lung tissue from pigs infected with Actinobacillus pleuropneumoniae
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Podolska Agnieszka, Anthon Christian, Bak Mads, Tommerup Niels, Skovgaard Kerstin, Heegaard Peter MH, Gorodkin Jan, Cirera Susanna, and Fredholm Merete
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MicroRNA ,RNAseq ,High throughput sequencing ,RT-qPCR ,Actinobacillus pleuropneumoniae ,Pig ,Pleuropneumonia ,Biotechnology ,TP248.13-248.65 ,Genetics ,QH426-470 - Abstract
Abstract Background MicroRNAs (miRNAs) are a class of non-protein-coding genes that play a crucial regulatory role in mammalian development and disease. Whereas a large number of miRNAs have been annotated at the structural level during the latest years, functional annotation is sparse. Actinobacillus pleuropneumoniae (APP) causes serious lung infections in pigs. Severe damage to the lungs, in many cases deadly, is caused by toxins released by the bacterium and to some degree by host mediated tissue damage. However, understanding of the role of microRNAs in the course of this infectious disease in porcine is still very limited. Results In this study, the RNA extracted from visually unaffected and necrotic tissue from pigs infected with Actinobacillus pleuropneumoniae was subjected to small RNA deep sequencing. We identified 169 conserved and 11 candidate novel microRNAs in the pig. Of these, 17 were significantly up-regulated in the necrotic sample and 12 were down-regulated. The expression analysis of a number of candidates revealed microRNAs of potential importance in the innate immune response. MiR-155, a known key player in inflammation, was found expressed in both samples. Moreover, miR-664-5p, miR-451 and miR-15a appear as very promising candidates for microRNAs involved in response to pathogen infection. Conclusions This is the first study revealing significant differences in composition and expression profiles of miRNAs in lungs infected with a bacterial pathogen. Our results extend annotation of microRNA in pig and provide insight into the role of a number of microRNAs in regulation of bacteria induced immune and inflammatory response in porcine lung.
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- 2012
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13. Human pathways in animal models: possibilities and limitations.
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Doncheva, Nadezhda T, Palasca, Oana, Yarani, Reza, Litman, Thomas, Anthon, Christian, Groenen, Martien A M, Stadler, Peter F, Pociot, Flemming, Jensen, Lars J, and Gorodkin, Jan
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- 2021
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14. Toward understanding nephelauxetism: interelectronic repulsion in gaseous d q ions computed by Kohn–Sham DFT
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Anthon, Christian and Schäffer, Claus E.
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- 2002
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15. Epigenetic and Transcriptomic Characterization of Pure Adipocyte Fractions From Obese Pigs Identifies Candidate Pathways Controlling Metabolism.
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Jacobsen, Mette Juul, Havgaard, Jakob H., Anthon, Christian, Mentzel, Caroline M. Junker, Cirera, Susanna, Krogh, Poula Maltha, Pundhir, Sachin, Karlskov-Mortensen, Peter, Bruun, Camilla S., Lesnik, Philippe, Guerin, Maryse, Gorodkin, Jan, Jørgensen, Claus B., Fredholm, Merete, and Barrès, Romain
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METABOLIC regulation ,ADIPOGENESIS ,EPIGENETICS ,SWINE ,DNA methylation ,METABOLIC disorders ,BINDING sites - Abstract
Reprogramming of adipocyte function in obesity is implicated in metabolic disorders like type 2 diabetes. Here, we used the pig, an animal model sharing many physiological and pathophysiological similarities with humans, to perform in-depth epigenomic and transcriptomic characterization of pure adipocyte fractions. Using a combined DNA methylation capture sequencing and Reduced Representation bisulfite sequencing (RRBS) strategy in 11 lean and 12 obese pigs, we identified in 3529 differentially methylated regions (DMRs) located at close proximity to-, or within genes in the adipocytes. By sequencing of the transcriptome from the same fraction of isolated adipocytes, we identified 276 differentially expressed transcripts with at least one or more DMR. These transcripts were over-represented in gene pathways related to MAPK, metabolic and insulin signaling. Using a candidate gene approach, we further characterized 13 genes potentially regulated by DNA methylation and identified putative transcription factor binding sites that could be affected by the differential methylation in obesity. Our data constitute a valuable resource for further investigations aiming to delineate the epigenetic etiology of metabolic disorders. [ABSTRACT FROM AUTHOR]
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- 2019
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16. P135 MAJOR GENE REGULATORS AFFECTED IN COLON AND BLOOD OF DEXTRAN SODIUM SULFATE ACUTE COLITIS MURINE MODEL
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Yarani, Reza, Palasca, Oana, Doncheva, Nadezhda Tsankova, Anthon, Christian, Pilecki, Bartosz, Litman, Thomas, Holmskov, Uffe, Jensen, Lars Juhl, Gorodkin, Jan, and Pociot, Flemming
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- 2020
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17. A new tripodal ligand system with steric and electronic modularity for uranium coordination chemistry
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Bart, Suzanne C., Heinemann, Frank W., Anthon, Christian, Hauser, Christina, and Meyer, Karsten
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Argon -- Chemical properties ,Argon -- Structure ,Oxidation-reduction reaction -- Analysis ,Spectrum analysis -- Usage ,X-ray crystallography -- Usage ,Chemistry - Published
- 2009
18. Carbon dioxide activation with sterically pressured mid- and high-valent uranium complexes
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Bart, Suzanne C., Anthon, Christian, Heinemann, Frank W., Bill, Eckhard, Edelstein, Norman M., and Meyer, Karsten
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Carbon dioxide -- Structure ,Carbon dioxide -- Chemical properties ,Uranium -- Structure ,Uranium -- Chemical properties ,Arylation -- Research ,Chemistry - Abstract
Sterically pressured mid- to high-valent uranium complexes with an aryloxide substituted triazacyclononane ligand scaffold are analyzed for carbon dioxide activation and transformation chemistry. The molecular structures of the synthesized uranium carbamate complexes have highlighted the different reactivities due to the steric pressure introduced by the alkyl derivatized tris(aryloxide) triazacyclononane ligand.
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- 2008
19. Structural and spectroscopic characterization of a charge-separated uranium benzophenone ketyl radical complex
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Lam, Oanh P., Anthon, Christian, Heinemann, Frank W., O'Connor, Joseph M., and Meyer, Karsten
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Benzophenone -- Chemical properties ,Organometallic compounds -- Chemical properties ,Uranium -- Chemical properties ,Chemistry - Abstract
Several studies are conducted to explain the structural and spectroscopic characterization of a charge-separated uranium benzophenone ketyl radical complex. The complex is shown to be highly reactive, giving out methoxide complex on isolation.
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- 2008
20. An average-of-configuration method for using Kohn-Sham density functional theory in modeling ligand-field theory
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Anthon, Christian, Bendix, Jesper, and Schaffer, Claus E.
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Chemistry, Inorganic -- Research ,Inorganic compounds -- Composition ,Density functionals -- Usage ,Methodology -- Analysis ,Ligand field theory -- Usage ,Ligand field theory -- Analysis ,Chemistry - Abstract
Research has been conducted on ligand-field theory. The authors discuss the use of Amsterdam Density Functional package in constraining Kohn-Sham density functional theory in order to define the transition from Kohn-Sham density functional theory to ligand-field theory in the parametrical d (super)q model form.
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- 2003
21. IFN-λ and microRNAs are important modulators of the pulmonary innate immune response against influenza A (H1N2) infection in pigs.
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Brogaard, Louise, Larsen, Lars E., Heegaard, Peter M. H., Anthon, Christian, Gorodkin, Jan, Dürrwald, Ralf, and Skovgaard, Kerstin
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INFLUENZA A virus ,MICRORNA genetics ,IMMUNE response ,IMMUNOLOGY ,NON-coding RNA - Abstract
The innate immune system is paramount in the response to and clearance of influenza A virus (IAV) infection in non-immune individuals. Known factors include type I and III interferons and antiviral pathogen recognition receptors, and the cascades of antiviral and pro- and anti-inflammatory gene expression they induce. MicroRNAs (miRNAs) are increasingly recognized to participate in post-transcriptional modulation of these responses, but the temporal dynamics of how these players of the antiviral innate immune response collaborate to combat infection remain poorly characterized. We quantified the expression of miRNAs and protein coding genes in the lungs of pigs 1, 3, and 14 days after challenge with swine IAV (H1N2). Through RT-qPCR we observed a 400-fold relative increase in IFN-λ3 gene expression on day 1 after challenge, and a strong interferon-mediated antiviral response was observed on days 1 and 3 accompanied by up-regulation of genes related to the pro-inflammatory response and apoptosis. Using small RNA sequencing and qPCR validation we found 27 miRNAs that were differentially expressed after challenge, with the highest number of regulated miRNAs observed on day 3. In contrast, the number of protein coding genes found to be regulated due to IAV infection peaked on day 1. Pulmonary miRNAs may thus be aimed at fine-tuning the initial rapid inflammatory response after IAV infection. Specifically, we found five miRNAs (ssc-miR-15a, ssc-miR-18a, ssc-miR-21, ssc-miR-29b, and hsa-miR-590-3p)–four known porcine miRNAs and one novel porcine miRNA candidate–to be potential modulators of viral pathogen recognition and apoptosis. A total of 11 miRNAs remained differentially expressed 14 days after challenge, at which point the infection had cleared. In conclusion, the results suggested a role for miRNAs both during acute infection as well as later, with the potential to influence lung homeostasis and susceptibility to secondary infections in the lungs of pigs after IAV infection. [ABSTRACT FROM AUTHOR]
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- 2018
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22. RAIN: RNA-protein Association and Interaction Networks.
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Junge, Alexander, Refsgaard, Jan C., Garde, Christian, Xiaoyong Pan, Santos, Alberto, Alkan, Ferhat, Anthon, Christian, von Mering, Christian, Workman, Christopher T., Jensen, Lars Juhl, and Gorodkin, Jan
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RNA-protein interactions ,PROTEIN-protein interactions ,WEB-based user interfaces ,PREDICTION models ,DOWNLOADING - Abstract
Protein association networks can be inferred from a range of resources including experimental data, literature mining and computational predictions. These types of evidence are emerging for non-coding RNAs (ncRNAs) aswell. However, integration of ncRNAs into protein association networks is challenging due to data heterogeneity. Here, we present a database of ncRNA-RNA and ncRNA-protein interactions and its integration with the STRING database of protein-protein interactions. These ncRNA associations cover four organisms and have been established from curated examples, experimental data, interaction predictions and automatic literaturemining. RAIN uses an integrative scoring scheme to assign a confidence score to each interaction. We demonstrate that RAIN outperforms the underlying microRNA-target predictions in inferring ncRNA interactions. RAIN can be operated through an easily accessibleweb interface and all interaction data can be downloaded. [ABSTRACT FROM AUTHOR]
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- 2017
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23. The Bacillaceae-1 RNA motif comprises two distinct classes.
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González-Tortuero, Enrique, Anthon, Christian, Havgaard, Jakob H., Geissler, Adrian S., Breüner, Anne, Hjort, Carsten, Gorodkin, Jan, and Seemann, Stefan E.
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RNA , *RIBOSOMAL RNA , *NON-coding RNA , *BACILLUS subtilis , *THERMODYNAMIC potentials , *BACILLUS (Bacteria) - Abstract
• The Bacillaceae-1 RNA motif consists of two distinct classes. • Reverse complementary B-1 structure upstream of 16S rRNA has one stable motif. • Intergenic B-1 motifs have high structure diversity and may act as structural switch. Non-coding RNAs are key regulatory players in bacteria. Many computationally predicted non-coding RNAs, however, lack functional associations. An example is the Bacillaceae-1 RNA motif, whose Rfam model consists of two hairpin loops. We find the motif conserved in nine of 13 non-pathogenic strains of the genus Bacillus but only in one pathogenic strain. To elucidate functional characteristics, we studied 118 hits of the Rfam model in 11 Bacillus spp. and found two distinct classes based on the ensemble diversity of their RNA secondary structure and the genomic context concerning the ribosomal RNA (rRNA) cluster. Forty hits are associated with the rRNA cluster, of which all 19 hits upstream flanking of 16S rRNA have a reverse complementary structure of low structural diversity. Fifty-two hits have large ensemble diversity, of which 38 are located between two coding genes. For eight hits in Bacillus subtilis , we investigated public expression data under various conditions and observed either the forward or the reverse complementary motif expressed. Five hits are associated with the rRNA cluster. Four of them are located upstream of the 16S rRNA and are not transcriptionally active, but instead, their reverse complements with low structural diversity are expressed together with the rRNA cluster. The three other hits are located between two coding genes in non-conserved genomic loci. Two of them are independently expressed from their surrounding genes and are structurally diverse. In summary, we found that Bacillaceae-1 RNA motifs upstream flanking of ribosomal RNA clusters tend to have one stable structure with the reverse complementary motif expressed in B. subtilis. In contrast, a subgroup of intergenic motifs has the thermodynamic potential for structural switches. [ABSTRACT FROM AUTHOR]
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- 2022
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24. Tools and data services registry: a community effort to document bioinformatics resources.
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Ison, Jon, Rapacki, Kristoffer, Ménager, Hervé, Kalaš, Matúš, Rydza, Emil, Chmura, Piotr, Anthon, Christian, Beard, Niall, Berka, Karel, Bolser, Dan, Booth, Tim, Bretaudeau, Anthony, Brezovsky, Jan, Casadio, Rita, Cesareni, Gianni, Coppens, Frederik, Cornell, Michael, Cuccuru, Gianmauro, Davidsen, Kristian, and Della Vedova, Gianluca
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- 2016
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25. RNA 3D Modules in Genome-Wide Predictions of RNA 2D Structure.
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Theis, Corinna, Zirbel, Craig L., zu Siederdissen, Christian Höner, Anthon, Christian, Hofacker, Ivo L., Nielsen, Henrik, and Gorodkin, Jan
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RNA analysis ,TWO-dimensional models ,CHEMICAL structure ,FALSE discovery rate ,COMPARATIVE studies ,ESTIMATION theory - Abstract
Recent experimental and computational progress has revealed a large potential for RNA structure in the genome. This has been driven by computational strategies that exploit multiple genomes of related organisms to identify common sequences and secondary structures. However, these computational approaches have two main challenges: they are computationally expensive and they have a relatively high false discovery rate (FDR). Simultaneously, RNA 3D structure analysis has revealed modules composed of non-canonical base pairs which occur in non-homologous positions, apparently by independent evolution. These modules can, for example, occur inside structural elements which in RNA 2D predictions appear as internal loops. Hence one question is if the use of such RNA 3D information can improve the prediction accuracy of RNA secondary structure at a genome-wide level. Here, we use RNAz in combination with 3D module prediction tools and apply them on a 13-way vertebrate sequence-based alignment. We find that RNA 3D modules predicted by metaRNAmodules and JAR3D are significantly enriched in the screened windows compared to their shuffled counterparts. The initially estimated FDR of 47.0% is lowered to below 25% when certain 3D module predictions are present in the window of the 2D prediction. We discuss the implications and prospects for further development of computational strategies for detection of RNA 2D structure in genomic sequence. [ABSTRACT FROM AUTHOR]
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- 2015
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26. Gender and Obesity Specific MicroRNA Expression in Adipose Tissue from Lean and Obese Pigs.
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Mentzel, Caroline M. Junker, Anthon, Christian, Jacobsen, Mette J., Karlskov-Mortensen, Peter, Bruun, Camilla S., Jørgensen, Claus B., Gorodkin, Jan, Cirera, Susanna, and Fredholm, Merete
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OBESITY genetics , *MICRORNA , *ADIPOSE tissues , *GENETIC regulation , *RNA sequencing , *LABORATORY swine ,SEX differences (Biology) - Abstract
Obesity is a complex condition that increases the risk of life threatening diseases such as cardiovascular disease and diabetes. Studying the gene regulation of obesity is important for understanding the molecular mechanisms behind the obesity derived diseases and may lead to better intervention and treatment plans. MicroRNAs (miRNAs) are short non-coding RNAs regulating target mRNA by binding to their 3’UTR. They are involved in numerous biological processes and diseases, including obesity. In this study we use a mixed breed pig model designed for obesity studies to investigate differentially expressed miRNAs in subcutaneous adipose tissue by RNA sequencing (RNAseq). Both male and female pigs are included to explore gender differences. The RNAseq study shows that the most highly expressed miRNAs are in accordance with comparable studies in pigs and humans. A total of six miRNAs are differentially expressed in subcutaneous adipose tissue between the lean and obese group of pigs, and in addition gender specific significant differential expression is observed for a number of miRNAs. The differentially expressed miRNAs have been verified using qPCR. The results of these studies in general confirm the trends found by RNAseq. Mir-9 and mir-124a are significantly differentially expressed with large fold changes in subcutaneous adipose tissue between lean and obese pigs. Mir-9 is more highly expressed in the obese pigs with a fold change of 10 and a p-value < 0.001. Mir-124a is more highly expressed in the obese pigs with a fold change of 114 and a p-value < 0.001. In addition, mir-124a is significantly higher expressed in abdominal adipose tissue in male pigs with a fold change of 119 and a p-value < 0.05. Both miRNAs are also significantly higher expressed in the liver of obese male pigs where mir-124a has a fold change of 12 and mir-9 has a fold change of 1.6, both with p-values < 0.05. [ABSTRACT FROM AUTHOR]
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- 2015
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27. Structured RNAs and synteny regions in the pig genome.
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Anthon, Christian, Tafer, Hakim, Havgaard, Jakob H., Thomsen, Bo, Hedegaard, Jakob, Seemann, Stefan E., Pundhir, Sachin, Kehr, Stephanie, Bartschat, Sebastian, Nielsen, Mathilde, Nielsen, Rasmus O., Fredholm, Merete, Stadler, Peter F., and Gorodkin, Jan
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ANIMAL genetics , *NON-coding RNA , *GENOMES , *NUCLEOTIDE sequence , *CATALYTIC RNA , *LOCUS (Genetics) - Abstract
Background Annotating mammalian genomes for noncoding RNAs (ncRNAs) is nontrivial since far from all ncRNAs are known and the computational models are resource demanding. Currently, the human genome holds the best mammalian ncRNA annotation, a result of numerous efforts by several groups. However, a more direct strategy is desired for the increasing number of sequenced mammalian genomes of which some, such as the pig, are relevant as disease models and production animals. Results We present a comprehensive annotation of structured RNAs in the pig genome. Combining sequence and structure similarity search as well as class specific methods, we obtained a conservative set with a total of 3,391 structured RNA loci of which 1,011 and 2,314, respectively, hold strong sequence and structure similarity to structured RNAs in existing databases. The RNA loci cover 139 cis-regulatory element loci, 58 lncRNA loci, 11 conflicts of annotation, and 3,183 ncRNA genes. The ncRNA genes comprise 359 miRNAs, 8 ribozymes, 185 rRNAs, 638 snoRNAs, 1,030 snRNAs, 810 tRNAs and 153 ncRNA genes not belonging to the here fore mentioned classes. When running the pipeline on a local shuffled version of the genome, we obtained no matches at the highest confidence level. Additional analysis of RNA-seq data from a pooled library from 10 different pig tissues added another 165 miRNA loci, yielding an overall annotation of 3,556 structured RNA loci. This annotation represents our best effort at making an automated annotation. To further enhance the reliability, 571 of the 3,556 structured RNAs were manually curated by methods depending on the RNA class while 1,581 were declared as pseudogenes. We further created a multiple alignment of pig against 20 representative vertebrates, from which RNAz predicted 83,859 dec novo RNA loci with conserved RNA structures. 528 of the RNAz predictions overlapped with the homology based annotation or novel miRNAs. We further present a substantial synteny analysis which includes 1,004 lineage specific dec novo RNA loci and 4 ncRNA loci in the known annotation specific for Laurasiatheria (pig, cow, dolphin, horse, cat, dog, hedgehog). Conclusions We have obtained one of the most comprehensive annotations for structured ncRNAs of a mammalian genome, which is likely to play central roles in both health modelling and production. The core annotation is available in Ensembl 70 and the complete annotation is available at http://rth.dk/ resources/rnannotator/susscr102/version1.02. [ABSTRACT FROM AUTHOR]
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- 2014
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28. Heterobimetallic Nitride Complexes from Terminal Chromium(V) Nitride Complexes: Hyperfine Coupling Increases with Distance.
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Bendix, Jesper, Anthon, Christian, Schau-Magnussen, Magnus, Brock-Nannestad, Theis, Vibenholt, Johan, Rehman, Muniza, and Sauer, Stephan P. A.
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- 2011
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29. Influence of steric pressure on the activation of carbon dioxide and related small molecules by uranium coordination complexes.
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Lam, Oanh P., Anthon, Christian, and Meyer, Karsten
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METAL complexes , *CARBON dioxide , *ACTIVATION (Chemistry) , *URANIUM , *CHEMICAL bonds , *METAL catalysts , *COORDINATION compounds , *DENSITY functionals - Abstract
Recent reports on new types of reactions and bonding using uranium coordination complexes have marked uranium as an effective candidate for small molecule activation and potentially as a key participant in catalytic processes. This review discusses the advantages of employing uranium in coordination chemistry, with emphasis on the importance of ligand design and the promotion of unusual chemical transformations by steric pressure. The activation of industrially relevant C1 feedstocks such as CO and CO2by uranium complexes with their exemplary abilities to stabilize highly reactive charge-separated complexes are highlighted in this article. Spectroscopic and DFT studies are also presented, demonstrating the important methods that are utilized for investigating the electronic properties of these uranium complexes. [ABSTRACT FROM AUTHOR]
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- 2009
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30. An Iron Nitride Complex.
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Vogel, Carola, Heinemann, Frank W., Sutter, Jörg, Anthon, Christian, and Meyer, Karsten
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- 2008
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31. Toward understanding nephelauxetism: interelectronic repulsion in gaseous dq ions computed by Kohn–Sham DFT
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Anthon, Christian and Schäffer, Claus E.
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DENSITY functionals , *IONS - Abstract
The nephelauxetic phenomenon is reviewed. So is the newest formulation of the Slater–Condon–Shortley model (SCS) for the multiplet term energies of atomic dq ions. This model is expressed as a sum of products of empirical parameters and their associated coefficient operators. The orthogonal-operators formalism is used by choosing Jørgensen''s spin-pairing energy parameter D as one of the repulsion parameters when the other parameter required by the SCS model is the Racah parameter B. By restricting the coefficient operators further so as to make them orthonormal, B changes into the new parameter E=(21/4)B. D accounts for the energy separation of eigenstates with different spin and/or seniority, E for the final separation into the spatially different eigenstates. The numerical values of D and E exhibit directly the relative contributions of D and E to the average configurational splitting. The parameter set {D, E} is equivalent to the SCS set {F2, F4} as well as to the Racah set {C, B} even though these sets are not associated with orthogonal operators so that cross products, as for instance CB, enter the expressions for the average configurational splitting. Moreover, neither conventional parameter set provides a visualizable interpretation of the energetic functioning of its parameters upon the eigenstate energy separations. The symmetry problem of the two-electron part of Kohn–Sham DFT is discussed in the framework of the SCS model. With the future perspective of mimicking ligand-field theory and, in particular, of dealing with the full nephelauxetic phenomenon non-empirically, the atomic part of the phenomenon is handled by calculation of the parameters D and E successfully for numerous gaseous ions with 3dq configurations. The Amsterdam Density Functional package (ADF) has been used in a two-step procedure. First, all the Kohn–Sham self-consistent field d-orbitals of the 3dq configurations as well as all the inner core orbitals were determined using population numbers of q/10 for all the 3d-spin–orbitals, that is, by doing the average-of-configuration calculation. Secondly, all these orbitals were frozen in all the subsequent calculations on the same system. Here density distributions of α and β electrons were defined by integer occupation numbers of d-spin–orbitals corresponding to single Slater determinants. On grounds of principle, complex orbitals were found not to be usable. The ADF energy associated with a real determinant was—apart from an additive constant—taken to correspond to the expectation value of the interelectronic repulsion operator acting on the dq part of this determinant. A characteristic property of the method is that the energy is expressed by a sum over contributions from the Coulomb and the exchange-correlation functional. It has turned out that for real d-orbitals both of these terms independently obey the symmetry restrictions as well as the special SCS restrictions of the dq assumption. However, the two functionals are not commensurable. They give different parametric results. Nevertheless, by averaging the total energy results from using a gradient-corrected (GC) set of functionals over the configuration dq, values for the SCS parameters that are better than those of Hartree–Fock calculations are obtained. In the local density approximation (LDA) the exchange-correlation functionals were found to provide the same energy for all real Slater determinants with the same value for MS, which means that the exchange-correlation part of the energy corresponds to B=E=0. However, the Coulomb functional invariably exaggerates the values of the E parameter so that LDA functionals end up giving fairly reasonable values of E, as well as D. We have obtained a complete bridge between KS-DFT in the form of ADF and the atomic part of ligand-field theory. [Copyright &y& Elsevier]
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- 2002
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32. Multiple Sequence Alignments Enhance Boundary Definition of RNA Structures.
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Sabarinathan, Radhakrishnan, Anthon, Christian, Gorodkin, Jan, and Seemann, Stefan E.
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NUCLEOTIDE sequence , *SEQUENCE alignment , *NON-coding RNA , *PROTEIN binding , *PREDICTION models - Abstract
Self-contained structured domains of RNA sequences have often distinct molecular functions. Determining the boundaries of structured domains of a non-coding RNA (ncRNA) is needed for many ncRNA gene finder programs that predict RNA secondary structures in aligned genomes because these methods do not necessarily provide precise information about the boundaries or the location of the RNA structure inside the predicted ncRNA. Even without having a structure prediction, it is of interest to search for structured domains, such as for finding common RNA motifs in RNA-protein binding assays. The precise definition of the boundaries are essential for downstream analyses such as RNA structure modelling, e.g., through covariance models, and RNA structure clustering for the search of common motifs. Such efforts have so far been focused on single sequences, thus here we present a comparison for boundary definition between single sequence and multiple sequence alignments. We also present a novel approach, named RNAbound, for finding the boundaries that are based on probabilities of evolutionarily conserved base pairings. We tested the performance of two different methods on a limited number of Rfam families using the annotated structured RNA regions in the human genome and their multiple sequence alignments created from 14 species. The results show that multiple sequence alignments improve the boundary prediction for branched structures compared to single sequences independent of the chosen method. The actual performance of the two methods differs on single hairpin structures and branched structures. For the RNA families with branched structures, including transfer RNA (tRNA) and small nucleolar RNAs (snoRNAs), RNAbound improves the boundary predictions using multiple sequence alignments to median differences of −6 and −11.5 nucleotides (nts) for left and right boundary, respectively (window size of 200 nts). [ABSTRACT FROM AUTHOR]
- Published
- 2018
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33. WebCircRNA: Classifying the Circular RNA Potential of Coding and Noncoding RNA.
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Pan, Xiaoyong, Xiong, Kai, Anthon, Christian, Hyttel, Poul, Freude, Kristine K., Jensen, Lars Juhl, and Gorodkin, Jan
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CIRCULAR RNA ,GENETIC regulation ,CELL differentiation ,STEM cells ,RANDOM forest algorithms - Abstract
Circular RNAs (circRNAs) are increasingly recognized to play crucial roles in post-transcriptional gene regulation including functioning as microRNA (miRNA) sponges or as wide-spread regulators, for example in stem cell differentiation. It is therefore highly relevant to identify if a transcript of interest can also function as a circRNA. Here, we present a user-friendly web server that predicts if coding and noncoding RNAs have circRNA isoforms and whether circRNAs are expressed in stem cells. The predictions are made by random forest models using sequence-derived features as input. The output scores are converted to fractiles, which are used to assess the circRNA and stem cell potential. The performances of the three models are reported as the area under the receiver operating characteristic (ROC) curve and are 0.82 for coding genes, 0.89 for long noncoding RNAs (lncRNAs) and 0.72 for stem cell expression. We present WebCircRNA for quick evaluation of human genes and transcripts for their circRNA potential, which can be essential in several contexts. [ABSTRACT FROM AUTHOR]
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- 2018
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34. CRISPR-Cas9 off-targeting assessment with nucleic acid duplex energy parameters.
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Alkan, Ferhat, Wenzel, Anne, Anthon, Christian, Havgaard, Jakob Hull, and Gorodkin, Jan
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- 2018
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35. Tools and data services registry: a community effort to document bioinformatics resources
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Callum Smith, Paolo Uva, Thomas Gatter, Peter Løngreen, Peter Juvan, Hans Ienasescu, Giuseppe Profiti, Aleksandra Nenadic, Kristoffer Rapacki, Chris Morris, Paola Roncaglia, Steffen Möller, Laura Emery, Søren Brunak, Maria Maddalena Sperotto, Heinz Stockinger, Kristian Davidsen, Federico Zambelli, Helen Parkinson, Olivia Doppelt-Azeroual, Luana Licata, Tatyana Goldberg, Andrea Schafferhans, Elisabeth Gasteiger, Emil Karol Rydza, Camille Laibe, Victor De La Torre, Marie Grosjean, Manuela Helmer-Citterich, Hervé Ménager, Radka Svobodová Vařeková, Rafael C. Jimenez, Martin Closter Jespersen, Anthony Bretaudeau, Jan Brezovsky, Tunca Doğan, Matúš Kalaš, Peter M. Rice, Ivan Mičetić, Rune Møllegaard Friborg, Maximilian Koch, Silvio C. E. Tosatto, Nick Juty, Björn Grüning, Gianmauro Cuccuru, Frederik Coppens, Gianni Cesareni, Jon Ison, Rabie Saidi, Sébastien Moretti, Rita Casadio, Gert Vriend, Guy Yachdav, Niall Beard, Timothy F. Booth, Michael Cornell, Piotr Jaroslaw Chmura, Veit Schwämmle, Karel Berka, Dan Bolser, Vassilios Ioannidis, Jing-Woei Li, Burkhard Rost, Gianluca Della Vedova, Fabien Mareuil, Hedi Peterson, Allegra Via, Paolo Romano, Christian Anthon, Technical University of Denmark [Lyngby] (DTU), Institut Pasteur de Madagascar, Réseau International des Instituts Pasteur (RIIP), University of Bergen (UIB), University of Copenhagen = Københavns Universitet (KU), University of Manchester, Palacky University, European Bioinformatics Institute, NEBC Wallingford, Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Institut National de la Recherche Agronomique (INRA)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, Masaryk University, University of Bologna, Università degli Studi di Roma Tor Vergata [Roma], Ghent University [Belgium] (UGENT), Flanders Institute for Biotechnology, CRS4 Bioinformat, Università degli studi di Milano-Bicocca, Swiss Institute of Bioinformatics, Universität Bielefeld = Bielefeld University, Tumor Biology Center, Centre National de la Recherche Scientifique (CNRS), University of Freiburg, University of Ljubljana, The Chinese University of Hong Kong [Hong Kong], Universita degli Studi di Padova, Bioinformatics Research Centre, Université de Lausanne, CCLRC Daresbury Laboratory, Universität zu Lübeck [Lübeck] - University of Lübeck [Lübeck], Universität Rostock, University of Tartu, Imperial College London, IRCCS Azienda Ospedaliera Universitaria Integrata San Martino (IRCCS AOU San Martino), University of Southern Denmark (SDU), WTCHG, Central European Institute of Technology [Brno] (CEITEC), Instituto Nacional de Bioinformática, Sapienza University of Rome (DIAG), Consiglio Nazionale delle Ricerche, University of Milan, Radboud University Nijmegen, Ison, J, Rapacki, K, Ménager, H, Kalaš, M, Rydza, E, Chmura, P, Anthon, C, Beard, N, Berka, K, Bolser, D, Booth, T, Bretaudeau, A, Brezovsky, J, Casadio, R, Cesareni, G, Coppens, F, Cornell, M, Cuccuru, G, Davidsen, K, DELLA VEDOVA, G, Dogan, T, Doppelt Azeroual, O, Emery, L, Gasteiger, E, Gatter, T, Goldberg, T, Grosjean, M, Grüning, B, Helmer Citterich, M, Ienasescu, H, Ioannidis, V, Jespersen, M, Jimenez, R, Juty, N, Juvan, P, Koch, M, Laibe, C, Li, J, Licata, L, Mareuil, F, Mičetić, I, Friborg, R, Moretti, S, Morris, C, Möller, S, Nenadic, A, Peterson, H, Profiti, G, Rice, P, Romano, P, Roncaglia, P, Saidi, R, Schafferhans, A, Schwämmle, V, Smith, C, Sperotto, M, Stockinger, H, Vařeková, R, Tosatto, S, de la Torre, V, Uva, P, Via, A, Yachdav, G, Zambelli, F, Vriend, G, Rost, B, Parkinson, H, Løngreen, P, Brunak, S, University of Bergen (UiB), Palacky University Olomouc, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Masaryk University [Brno] (MUNI), Universiteit Gent = Ghent University [Belgium] (UGENT), Università degli Studi di Milano-Bicocca [Milano] (UNIMIB), Swiss Institute of Bioinformatics [Lausanne] (SIB), Université de Lausanne (UNIL), Universität zu Lübeck [Lübeck], Central European Institute of Technology [Brno] (CEITEC MU), Brno University of Technology [Brno] (BUT), Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome], Danmarks Tekniske Universitet = Technical University of Denmark (DTU), University of Copenhagen = Københavns Universitet (UCPH), Institut National de la Recherche Agronomique (INRA)-Université de Rennes (UR)-AGROCAMPUS OUEST, University of Bologna/Università di Bologna, Universiteit Gent = Ghent University (UGENT), Università degli Studi di Milano-Bicocca = University of Milano-Bicocca (UNIMIB), Université de Lausanne = University of Lausanne (UNIL), Università degli Studi di Padova = University of Padua (Unipd), Universität zu Lübeck = University of Lübeck [Lübeck], Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome] (UNIROMA), Università degli Studi di Milano = University of Milan (UNIMI), Ison, Jon, Rapacki, Kristoffer, Ménager, Hervé, Kalaš, Matúš, Rydza, Emil, Chmura, Piotr, Anthon, Christian, Beard, Niall, Berka, Karel, Bolser, Dan, Booth, Tim, Bretaudeau, Anthony, Brezovsky, Jan, Casadio, Rita, Cesareni, Gianni, Coppens, Frederik, Cornell, Michael, Cuccuru, Gianmauro, Davidsen, Kristian, Vedova, Gianluca Della, Dogan, Tunca, Doppelt-Azeroual, Olivia, Emery, Laura, Gasteiger, Elisabeth, Gatter, Thoma, Goldberg, Tatyana, Grosjean, Marie, Grüning, Björn, Helmer-Citterich, Manuela, Ienasescu, Han, Ioannidis, Vassilio, Jespersen, Martin Closter, Jimenez, Rafael, Juty, Nick, Juvan, Peter, Koch, Maximilian, Laibe, Camille, Li, Jing-Woei, Licata, Luana, Mareuil, Fabien, Mičetić, Ivan, Friborg, Rune Møllegaard, Moretti, Sebastien, Morris, Chri, Möller, Steffen, Nenadic, Aleksandra, Peterson, Hedi, Profiti, Giuseppe, Rice, Peter, Romano, Paolo, Roncaglia, Paola, Saidi, Rabie, Schafferhans, Andrea, Schwämmle, Veit, Smith, Callum, Sperotto, Maria Maddalena, Stockinger, Heinz, Vařeková, Radka Svobodová, Tosatto, Silvio C E, de la Torre, Victor, Uva, Paolo, Via, Allegra, Yachdav, Guy, Zambelli, Federico, Vriend, Gert, Rost, Burkhard, Parkinson, Helen, Løngreen, Peter, and Brunak, Søren
- Subjects
0301 basic medicine ,[SDV]Life Sciences [q-bio] ,registry ,Bioinformatics ,computer.software_genre ,Matematikk og naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Systemutvikling og -arbeid: 426 [VDP] ,Task (project management) ,Documentation ,Data and Information ,Database Issue ,Registries ,bioinformatique ,Data Curation ,base de données ,Settore BIO/11 ,gestion de données ,tool ,SOFTWARE-DEVELOPMENT ,bioinformatics ,ddc ,outil informatique ,Tools and data services registry ,SEQANSWERS ,Web service ,MOLECULAR-BIOLOGY ,Biology ,Ecology and Environment ,03 medical and health sciences ,SDG 3 - Good Health and Well-being ,Genetics ,Implementation ,Dissemination ,Bioinformatikk / Bioinformatics ,Data curation ,bioinformatic ,business.industry ,Computational Biology ,Software ,Software development ,bioinformatics, tools, registry, elixir ,Biology and Life Sciences ,Mathematics and natural scienses: 400::Information and communication science: 420::System development and design: 426 [VDP] ,FRAMEWORK ,ELIXIR ,Settore BIO/18 - Genetica ,030104 developmental biology ,tools ,Data as a service ,COMPILATION ,business ,COLLECTION ,Nanomedicine Radboud Institute for Molecular Life Sciences [Radboudumc 19] ,computer ,WEB SERVICES ,LIFE SCIENCES - Abstract
Contains fulltext : 171819.pdf (Publisher’s version ) (Open Access) Life sciences are yielding huge data sets that underpin scientific discoveries fundamental to improvement in human health, agriculture and the environment. In support of these discoveries, a plethora of databases and tools are deployed, in technically complex and diverse implementations, across a spectrum of scientific disciplines. The corpus of documentation of these resources is fragmented across the Web, with much redundancy, and has lacked a common standard of information. The outcome is that scientists must often struggle to find, understand, compare and use the best resources for the task at hand.Here we present a community-driven curation effort, supported by ELIXIR-the European infrastructure for biological information-that aspires to a comprehensive and consistent registry of information about bioinformatics resources. The sustainable upkeep of this Tools and Data Services Registry is assured by a curation effort driven by and tailored to local needs, and shared amongst a network of engaged partners.As of November 2015, the registry includes 1785 resources, with depositions from 126 individual registrations including 52 institutional providers and 74 individuals. With community support, the registry can become a standard for dissemination of information about bioinformatics resources: we welcome everyone to join us in this common endeavour. The registry is freely available at https://bio.tools.
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36. Cross-species high-resolution transcriptome profiling suggests biomarkers and therapeutic targets for ulcerative colitis.
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Yarani R, Palasca O, Doncheva NT, Anthon C, Pilecki B, Svane CAS, Mirza AH, Litman T, Holmskov U, Bang-Berthelsen CH, Vilien M, Jensen LJ, Gorodkin J, and Pociot F
- Abstract
Background: Ulcerative colitis (UC) is a disorder with unknown etiology, and animal models play an essential role in studying its molecular pathophysiology. Here, we aim to identify common conserved pathological UC-related gene expression signatures between humans and mice that can be used as treatment targets and/or biomarker candidates. Methods: To identify differentially regulated protein-coding genes and non-coding RNAs, we sequenced total RNA from the colon and blood of the most widely used dextran sodium sulfate Ulcerative colitis mouse. By combining this with public human Ulcerative colitis data, we investigated conserved gene expression signatures and pathways/biological processes through which these genes may contribute to disease development/progression. Results: Cross-species integration of human and mouse Ulcerative colitis data resulted in the identification of 1442 genes that were significantly differentially regulated in the same direction in the colon and 157 in blood. Of these, 51 genes showed consistent differential regulation in the colon and blood. Less known genes with importance in disease pathogenesis, including SPI1, FPR2, TYROBP, CKAP4, MCEMP1, ADGRG3, SLC11A1, and SELPLG, were identified through network centrality ranking and validated in independent human and mouse cohorts. Conclusion: The identified Ulcerative colitis conserved transcriptional signatures aid in the disease phenotyping and future treatment decisions, drug discovery, and clinical trial design., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Yarani, Palasca, Doncheva, Anthon, Pilecki, Svane, Mirza, Litman, Holmskov, Bang-Berthelsen, Vilien, Jensen, Gorodkin and Pociot.)
- Published
- 2023
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37. BSGatlas: a unified Bacillus subtilis genome and transcriptome annotation atlas with enhanced information access.
- Author
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Geissler AS, Anthon C, Alkan F, González-Tortuero E, Poulsen LD, Kallehauge TB, Breüner A, Seemann SE, Vinther J, and Gorodkin J
- Subjects
- Access to Information, Databases, Genetic, Gene Expression Profiling, Operon, RNA, Untranslated genetics, Sequence Analysis, RNA, Web Browser, Bacillus subtilis genetics, Computational Biology methods, Molecular Sequence Annotation methods
- Abstract
A large part of our current understanding of gene regulation in Gram-positive bacteria is based on Bacillus subtilis , as it is one of the most well studied bacterial model systems. The rapid growth in data concerning its molecular and genomic biology is distributed across multiple annotation resources. Consequently, the interpretation of data from further B. subtilis experiments becomes increasingly challenging in both low- and large-scale analyses. Additionally, B. subtilis annotation of structured RNA and non-coding RNA (ncRNA), as well as the operon structure, is still lagging behind the annotation of the coding sequences. To address these challenges, we created the B. subtilis genome atlas, BSGatlas, which integrates and unifies multiple existing annotation resources. Compared to any of the individual resources, the BSGatlas contains twice as many ncRNAs, while improving the positional annotation for 70 % of the ncRNAs. Furthermore, we combined known transcription start and termination sites with lists of known co-transcribed gene sets to create a comprehensive transcript map. The combination with transcription start/termination site annotations resulted in 717 new sets of co-transcribed genes and 5335 untranslated regions (UTRs). In comparison to existing resources, the number of 5' and 3' UTRs increased nearly fivefold, and the number of internal UTRs doubled. The transcript map is organized in 2266 operons, which provides transcriptional annotation for 92 % of all genes in the genome compared to the at most 82 % by previous resources. We predicted an off-target-aware genome-wide library of CRISPR-Cas9 guide RNAs, which we also linked to polycistronic operons. We provide the BSGatlas in multiple forms: as a website (https://rth.dk/resources/bsgatlas/), an annotation hub for display in the UCSC genome browser, supplementary tables and standardized GFF3 format, which can be used in large scale -omics studies. By complementing existing resources, the BSGatlas supports analyses of the B. subtilis genome and its molecular biology with respect to not only non-coding genes but also genome-wide transcriptional relationships of all genes.
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- 2021
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38. Quality Assessment of Domesticated Animal Genome Assemblies.
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Seemann SE, Anthon C, Palasca O, and Gorodkin J
- Abstract
The era of high-throughput sequencing has made it relatively simple to sequence genomes and transcriptomes of individuals from many species. In order to analyze the resulting sequencing data, high-quality reference genome assemblies are required. However, this is still a major challenge, and many domesticated animal genomes still need to be sequenced deeper in order to produce high-quality assemblies. In the meanwhile, ironically, the extent to which RNAseq and other next-generation data is produced frequently far exceeds that of the genomic sequence. Furthermore, basic comparative analysis is often affected by the lack of genomic sequence. Herein, we quantify the quality of the genome assemblies of 20 domesticated animals and related species by assessing a range of measurable parameters, and we show that there is a positive correlation between the fraction of mappable reads from RNAseq data and genome assembly quality. We rank the genomes by their assembly quality and discuss the implications for genotype analyses.
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- 2016
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39. Synthesis and molecular structure of Cr(salen)(mu-N)RhCl(COD): the first example of a heterobimetallic nitride-bridged complex containing chromium.
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Vibenholt J, Magnussen M, Anthon C, and Bendix J
- Abstract
Five-coordinate Cr(N)(salen) {salen is 2,2'-[ethane-1,2-diylbis(nitrilomethylidyne)]diphenolate} reacts with [RhCl(COD)](2) (COD is 1,5-cyclooctadiene) to yield the heterobimetallic nitride-bridged title compound, namely chlorido-2kappaCl-[2(eta(4))-1,5-cyclooctadiene]{2,2'-[ethane-1,2-diylbis(nitrilomethylidyne)]diphenolato-1kappa(4)O,N,N',O'}-mu-nitrido-1:2kappa(2)N:N-chromium(V)rhodium(I), [CrRh(C(16)H(14)N(2)O(2))ClN(C(8)H(12))]. The Cr-N bond of 1.5936 (14) A is elongated by only 0.035 A compared to the terminal Cr-N bond in the precursor. The nitride bridge is close to being linear [173.03 (9) degrees] and the Rh-N bond of 1.9594 (14) A is very short for a monodentate nitrogen-donor ligand, indicating significant pi-acceptor character of the Cr[triple bond]N group.
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- 2010
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40. An iron nitride complex.
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Vogel C, Heinemann FW, Sutter J, Anthon C, and Meyer K
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- Crystallography, X-Ray, Electrons, Iron Compounds chemistry, Models, Molecular, Molecular Structure, Spectrum Analysis, Iron Compounds chemical synthesis, Nitric Acid chemistry
- Published
- 2008
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