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2. MicroRNA or Not MicroRNA?

Author

Langenberger, David, Bartschat, Sebastian, Hertel, Jana, Hoffmann, Steve, Tafer, Hakim, Stadler, Peter F., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Istrail, Sorin, editor, Pevzner, Pavel, editor, Waterman, Michael S., editor, Norberto de Souza, Osmar, editor, Telles, Guilherme P., editor, and Palakal, Mathew, editor

Published
2011
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3. Introducing evolutionary biologists to the analysis of big data: guidelines to organize extended bioinformatics training courses

Author

Faria, Rui, Triant, Deborah, Perdomo-Sabogal, Alvaro, Overduin, Bert, Bleidorn, Christoph, Santana, Clara Isabel Bermudez, Langenberger, David, Dall’Olio, Giovanni Marco, Indrischek, Henrike, Aerts, Jan, Engelhardt, Jan, Engelken, Johannes, Liebal, Katja, Fasold, Mario, Robb, Sofia, Grath, Sonja, Kolora, Sree Rohit Raj, Carvalho, Tiago, Salzburger, Walter, Jovanovic, Vladimir, and Nowick, Katja

Published
2018
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4. The genomic and transcriptional landscape of primary central nervous system lymphoma

Author

Radke, Josefine, Ishaque, Naveed, Hostench, Xavier Pastor, Richter, Julia, Rosenstiel, Philip, Rosenwald, Andreas, Schilhabel, Markus, Schreiber, Stefanie, Vater, Inga, Wagener, Rabea, Siebert, Reiner, Bernhart, Stephan H, Binder, Hans, Borgoni, Simone, Doose, Gero, Eils, Roland, Hoffmann, Steve, Hopp, Lydia, Kleinheinz, Kortine, Kretzmer, Helene, Kreuz, Markus, Korbel, Jan, Langenberger, David, Loeffler, Markus, Juraeva, Dilafruz, Rosolowski, Maciej, Stadler, Peter F, Sungalee, Stephanie, Pritsch, Fabienne, Paramasivam, Nagarajan, Balasubramanian, Gnana Prakash, Schlesner, Matthias, Sahay, Shashwat, Weniger, Marc, Pehl, Debora, Koll, Randi, Radbruch, Helena, Osterloh, Anja, Korfel, Agnieszka, Misch, Martin, Onken, Julia, Faust, Katharina, Vajkoczy, Peter, Moskopp, Dag, Wang, Yawen, Jödicke, Andreas, Gu, Zuguang, Trümper, Lorenz, Anagnostopoulos, Ioannis, Lenze, Dido, Küppers, Ralf, Hummel, Michael, Schmitt, Clemens A, Wiestler, Otmar D, Wolf, Stephan, Unterberg, Andreas, Schumann, Elisa, Herold-Mende, Christel, Brors, Benedikt, Consortium, ICGC MMML-Seq, Wiemann, Stefan, Heppner, Frank, Wagner, Susanne, Haake, Andrea, Sieverling, Lina, Richter, Gesine, Lawerenz, Chris, Eils, Jürgen, Kerssemakers, Jules, Jaeger-Schmidt, Christina, Scholz, Ingrid, Bergmann, Anke K, Borst, Christoph, Braulke, Friederike, Uhrig, Sebastian, Burkhardt, Birgit, Claviez, Alexander, Dreyling, Martin, Eberth, Sonja, Einsele, Hermann, Frickhofen, Norbert, Haas, Siegfried, Hansmann, Martin-Leo, Karsch, Dennis, Klepl, Nicole, Hübschmann, Daniel, Kneba, Michael, Lisfeld, Jasmin, Mantovani-Löffler, Luisa, Rohde, Marius, Ott, German, Stadler, Christina, Staib, Peter, Stilgenbauer, Stephan, Zenz, Thorsten, Toprak, Umut H, Kube, Dieter, Klapper, Wolfram, Kostezka, Ulrike, Möller, Peter, Szczepanowski, Monika, Ammerpohl, Ole, Aukema, Sietse M, López, Cristina, Binder, Vera, Borkhardt, Arndt, Hoell, Jessica I, Leich, Ellen, Lichter, Peter, Nagel, Inga, Pischimariov, Jordan, Radlwimmer, Bernhard, Weniger, Marc (Beitragende*r), and Küppers, Ralf (Beitragende*r)

Subjects
Central Nervous System, Epstein-Barr Virus Infections, Herpesvirus 4, Human, Cancer Research, Multidisciplinary, genetics [Central Nervous System Neoplasms], Medizin, General Physics and Astronomy, pathology [Central Nervous System Neoplasms], Genomics, General Chemistry, metabolism [Lymphoma, Large B-Cell, Diffuse], General Biochemistry, Genetics and Molecular Biology, Central Nervous System Neoplasms, hemic and lymphatic diseases, metabolism [Central Nervous System], Humans, ddc:610, Lymphoma, Large B-Cell, Diffuse, ddc:500
Abstract

Primary lymphomas of the central nervous system (PCNSL) are mainly diffuse large B-cell lymphomas (DLBCLs) confined to the central nervous system (CNS). Molecular drivers of PCNSL have not been fully elucidated. Here, we profile and compare the whole-genome and transcriptome landscape of 51 CNS lymphomas (CNSL) to 39 follicular lymphoma and 36 DLBCL cases outside the CNS. We find recurrent mutations in JAK-STAT, NFkB, and B-cell receptor signaling pathways, including hallmark mutations in MYD88 L265P (67%) and CD79B (63%), and CDKN2A deletions (83%). PCNSLs exhibit significantly more focal deletions of HLA-D (6p21) locus as a potential mechanism of immune evasion. Mutational signatures correlating with DNA replication and mitosis are significantly enriched in PCNSL. TERT gene expression is significantly higher in PCNSL compared to activated B-cell (ABC)-DLBCL. Transcriptome analysis clearly distinguishes PCNSL and systemic DLBCL into distinct molecular subtypes. Epstein-Barr virus (EBV)+ CNSL cases lack recurrent mutational hotspots apart from IG and HLA-DRB loci. We show that PCNSL can be clearly distinguished from DLBCL, having distinct expression profiles, IG expression and translocation patterns, as well as specific combinations of genetic alterations.

Published
2022

5. Supplemental material Chromosome-level Thlaspi arvense genome provides new tools for translational research and for a newly domesticated cash cover crop of the cooler climates

Author

Carbonell-Bejerano, Pablo [0000-0002-7266-9665], Nunn, Adam, Rodríguez-Arévalo, Isaac, Tandukar, Zenith, Frels, Katherine, Contreras-Garrido, Andrián, Carbonell-Bejerano, Pablo, Zhang, Panpan, Ramos Cruz, Daniela, Jandrasits, Katharina, Lanz, Christa, Brusa, Anthony, Mirouze, Marie, Dorn, Kevin, Galbraith, David, Jarvis, Brice A., Sedbrook, John C., Wyse, Donald L., Otto, Christian, Langenberger, David, Stadler, Peter F., Weigel, Detlef, Marks, M. David, Anderson, James A., Becker, Claude, Chopra, Ratan, Carbonell-Bejerano, Pablo [0000-0002-7266-9665], Nunn, Adam, Rodríguez-Arévalo, Isaac, Tandukar, Zenith, Frels, Katherine, Contreras-Garrido, Andrián, Carbonell-Bejerano, Pablo, Zhang, Panpan, Ramos Cruz, Daniela, Jandrasits, Katharina, Lanz, Christa, Brusa, Anthony, Mirouze, Marie, Dorn, Kevin, Galbraith, David, Jarvis, Brice A., Sedbrook, John C., Wyse, Donald L., Otto, Christian, Langenberger, David, Stadler, Peter F., Weigel, Detlef, Marks, M. David, Anderson, James A., Becker, Claude, and Chopra, Ratan

Published
2022

6. Chromosome-level Thlaspi arvense genome provides new tools for translational research and for a newly domesticated cash cover crop of the cooler climates

Author

Minnesota Department of Agriculture, National Institute of Food and Agriculture (US), Department of Energy (US), Austrian Academy of Sciences, Max Planck Society, European Commission, European Research Council, Federal Ministry of Education and Research (Germany), Nunn, Adam, Rodríguez-Arévalo, Isaac, Tandukar, Zenith, Frels, Katherine, Contreras-Garrido, Andrián, Carbonell-Bejerano, Pablo, Zhang, Panpan, Ramos Cruz, Daniela, Jandrasits, Katharina, Lanz, Christa, Brusa, Anthony, Mirouze, Marie, Dorn, Kevin, Galbraith, David, Jarvis, Brice A., Sedbrook, John C., Wyse, Donald L., Otto, Christian, Langenberger, David, Stadler, Peter F., Weigel, Detlef, Marks, M. David, Anderson, James A., Becker, Claude, Chopra, Ratan, Minnesota Department of Agriculture, National Institute of Food and Agriculture (US), Department of Energy (US), Austrian Academy of Sciences, Max Planck Society, European Commission, European Research Council, Federal Ministry of Education and Research (Germany), Nunn, Adam, Rodríguez-Arévalo, Isaac, Tandukar, Zenith, Frels, Katherine, Contreras-Garrido, Andrián, Carbonell-Bejerano, Pablo, Zhang, Panpan, Ramos Cruz, Daniela, Jandrasits, Katharina, Lanz, Christa, Brusa, Anthony, Mirouze, Marie, Dorn, Kevin, Galbraith, David, Jarvis, Brice A., Sedbrook, John C., Wyse, Donald L., Otto, Christian, Langenberger, David, Stadler, Peter F., Weigel, Detlef, Marks, M. David, Anderson, James A., Becker, Claude, and Chopra, Ratan

Abstract

Thlaspi arvense (field pennycress) is being domesticated as a winter annual oilseed crop capable of improving ecosystems and intensifying agricultural productivity without increasing land use. It is a selfing diploid with a short life cycle and is amenable to genetic manipulations, making it an accessible field-based model species for genetics and epigenetics. The availability of a high-quality reference genome is vital for understanding pennycress physiology and for clarifying its evolutionary history within the Brassicaceae. Here, we present a chromosome-level genome assembly of var. MN106-Ref with improved gene annotation and use it to investigate gene structure differences between two accessions (MN108 and Spring32-10) that are highly amenable to genetic transformation. We describe non-coding RNAs, pseudogenes and transposable elements, and highlight tissue-specific expression and methylation patterns. Resequencing of forty wild accessions provided insights into genome-wide genetic variation, and QTL regions were identified for a seedling colour phenotype. Altogether, these data will serve as a tool for pennycress improvement in general and for translational research across the Brassicaceae.

Published
2022

7. Chromosome‐level Thlaspi arvense genome provides new tools for translational research and for a newly domesticated cash cover crop of the cooler climates

Author

Nunn, Adam, primary, Rodríguez‐Arévalo, Isaac, additional, Tandukar, Zenith, additional, Frels, Katherine, additional, Contreras‐Garrido, Adrián, additional, Carbonell‐Bejerano, Pablo, additional, Zhang, Panpan, additional, Ramos Cruz, Daniela, additional, Jandrasits, Katharina, additional, Lanz, Christa, additional, Brusa, Anthony, additional, Mirouze, Marie, additional, Dorn, Kevin, additional, Galbraith, David W, additional, Jarvis, Brice A., additional, Sedbrook, John C., additional, Wyse, Donald L., additional, Otto, Christian, additional, Langenberger, David, additional, Stadler, Peter F., additional, Weigel, Detlef, additional, Marks, M. David, additional, Anderson, James A., additional, Becker, Claude, additional, and Chopra, Ratan, additional

Published
2022
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8. Chromosome-level Thlaspi arvense genome provides new tools for translational research and for a newly domesticated cash cover crop of the cooler climates

Author

Nunn, Adam, Rodríguez-Arévalo, Isaac, Tandukar, Zenith, Frels, Katherine, Contreras-Garrido, Adrián, Carbonell-Bejerano, Pablo, Zhang, Panpan, Ramos-Cruz, Daniela, Jandrasits, Katharina, Lanz, Christa, Brusa, Anthony, Mirouze, Marie, Dorn, Kevin, Galbraith, David W., Jarvis, Brice A., Sedbrook, John C., Wyse, Donald L., Otto, Christian, Langenberger, David, Stadler, Peter F., Weigel, Detlef, Marks, M. David, Anderson, James A., Becker, Claude, Chopra, Ratan, Minnesota Department of Agriculture, National Institute of Food and Agriculture (US), Department of Energy (US), Austrian Academy of Sciences, Max Planck Society, European Commission, European Research Council, and Federal Ministry of Education and Research (Germany)

Subjects
Comparative genomics, Genetic mapping, Molecular Sequence Annotation, Plant Science, Genome annotations, Genomeassembly, Chromosomes, Thlaspi, Translational Research, Biomedical, genome assembly, Pennycress, Agronomy and Crop Science, Ecosystem, Genome, Plant, Biotechnology
Abstract

Thlaspi arvense (field pennycress) is being domesticated as a winter annual oilseed crop capable of improving ecosystems and intensifying agricultural productivity without increasing land use. It is a selfing diploid with a short life cycle and is amenable to genetic manipulations, making it an accessible field-based model species for genetics and epigenetics. The availability of a high-quality reference genome is vital for understanding pennycress physiology and for clarifying its evolutionary history within the Brassicaceae. Here, we present a chromosome-level genome assembly of var. MN106-Ref with improved gene annotation and use it to investigate gene structure differences between two accessions (MN108 and Spring32-10) that are highly amenable to genetic transformation. We describe non-coding RNAs, pseudogenes and transposable elements, and highlight tissue-specific expression and methylation patterns. Resequencing of forty wild accessions provided insights into genome-wide genetic variation, and QTL regions were identified for a seedling colour phenotype. Altogether, these data will serve as a tool for pennycress improvement in general and for translational research across the Brassicaceae., This material is based upon work that is supported by the Minnesota Department of Agriculture (J.A., K.F., R.C.) and by the National Institute of Food and Agriculture, U.S. Department of Agriculture, under award numbers 2018-67009-27374 (J.A., R.C., K.F.), and 2019-67009-29004 (M.D.M, J.S.) and the Agriculture and Food Research Initiative Competitive Grant No. 2019-69012-29851 (M.D.M, R.C., J.S.). This research was supported by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Genomics Science Program grant no. DE-SC0021286 (M.D.M, R.C.). This work was further funded by the Austrian Academy of Sciences (C.B., I.R.A., K.J., D.R.C.); the Max Planck Society (D.W., A.C.G., P.C.B., C.L.); the European Union’s Horizon 2020 research and innovation programme by the European Research Council (ERC), Grant Agreement No. 716823 ‘FEAR-SAP’ (I.R.A., C.B.), by the Marie Sklodowska-Curie ETN ‘EpiDiverse’, Grant Agreement No. 764965 (D.R.C., C.B.) and by Marie Sklodowska-Curie, Grant Agreement MSCA-IF No 797460 (P.C.B.); and the German Federal Ministry of Education and Research BMBF, Grant No. 031A538A, de.NBI-RBC (A.N., P.F.S.).

Published
2021

10. MethylScore, a pipeline for accurate and context-aware identification of differentially methylated regions from population-scale plant whole-genome bisulfite sequencing data

Author

Hüther, Patrick, primary, Hagmann, Jörg, additional, Nunn, Adam, additional, Kakoulidou, Ioanna, additional, Pisupati, Rahul, additional, Langenberger, David, additional, Weigel, Detlef, additional, Johannes, Frank, additional, Schultheiss, Sebastian J., additional, and Becker, Claude, additional

Published
2022
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12. Chromosome-level Thlaspi arvense genome provides new tools for translational research and for a newly domesticated cash cover crop of the cooler climates

Author

Nunn, Adam, primary, Rodríguez-Arévalo, Isaac, additional, Tandukar, Zenith, additional, Frels, Katherine, additional, Contreras-Garrido, Adrián, additional, Carbonell-Bejerano, Pablo, additional, Zhang, Panpan, additional, Ramos-Cruz, Daniela, additional, Jandrasits, Katharina, additional, Lanz, Christa, additional, Brusa, Anthony, additional, Mirouze, Marie, additional, Dorn, Kevin, additional, Jarvis, Brice, additional, Sedbrook, John, additional, Wyse, Donald L., additional, Otto, Christian, additional, Langenberger, David, additional, Stadler, Peter F., additional, Weigel, Detlef, additional, Marks, M. David, additional, Anderson, James A., additional, Becker, Claude, additional, and Chopra, Ratan, additional

Published
2021
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13. The landscape of genomic alterations across childhood cancers

Author

Grbner, Susanne N., Worst, Barbara C., Weischenfeldt, Joachim, Buchhalter, Ivo, Kleinheinz, Kortine, Rudneva, Vasilisa A., Johann, Pascal D., Balasubramanian, Gnana Prakash, Segura-Wang, Maia, Brabetz, Sebastian, Bender, Sebastian, Hutter, Barbara, Sturm, Dominik, Pfaff, Elke, Hbschmann, Daniel, Zipprich, Gideon, Heinold, Michael, Eils, Jrgen, Lawerenz, Christian, Erkek, Serap, Lambo, Sander, Waszak, Sebastian, Blattmann, Claudia, Borkhardt, Arndt, Kuhlen, Michaela, Eggert, Angelika, Fulda, Simone, Gessler, Manfred, Wegert, Jenny, Kappler, Roland, Baumhoer, Daniel, Burdach, Stefan, Kirschner-Schwabe, Renate, Kontny, Udo, Kulozik, Andreas E., Lohmann, Dietmar, Hettmer, Simone, Eckert, Cornelia, Bielack, Stefan, Nathrath, Michaela, Niemeyer, Charlotte, Richter, Gnther H., Schulte, Johannes, Siebert, Reiner, Westermann, Frank, Molenaar, Jan J., Vassal, Gilles, Witt, Hendrik, Lichter, Peter, Weber, Ursula, Eils, Roland, Korshunov, Andrey, Witt, Olaf, Pfister, Stefan, Reifenberger, Guido, Felsberg, Jrg, von Kalle, Christof, Schmidt, Manfred, Bartholom, Cynthia, Taylor, Michael, Jones, David, Jger, Natalie, Korbel, Jan, Sttz, Adrian, Rausch, Tobias, Radlwimmer, Bernhard, Yaspo, Marie-Laure, Lehrach, Hans, Warnatz, Hans-Jrg, Landgraf, Pablo, Brors, Benedikt, Zapatka, Marc, Wagner, Susanne, Haake, Andrea, Richter, Julia, Richter, Gesine, Lawerenz, Chris, Kerssemakers, Jules, Jaeger-Schmidt, Christina, Scholz, Ingrid, Bergmann, Anke K., Borst, Christoph, Burkhardt, Birgit, Claviez, Alexander, Dreyling, Martin, Eberth, Sonja, Einsele, Hermann, Frickhofen, Norbert, Haas, Siegfried, Hansmann, Martin-Leo, Karsch, Dennis, Kneba, Michael, Lisfeld, Jasmin, Mantovani-Lffler, Luisa, Rohde, Marius, Ott, German, Stadler, Christina, Staib, Peter, Stilgenbauer, Stephan, Trmper, Lorenz, Zenz, Thorsten, Kube, Dieter, Kppers, Ralf, Weniger, Marc, Hummel, Michael, Klapper, Wolfram, Kostezka, Ulrike, Lenze, Dido, Mller, Peter, Rosenwald, Andreas, Szczepanowski, Monika, Ammerpohl, Ole, Aukema, Sietse M., Binder, Vera, Hoell, Jessica I., Leich, Ellen, Lpez, Cristina, Nagel, Inga, Pischimariov, Jordan, Rosenstiel, Philip, Schilhabel, Markus, Schreiber, Stefan, Vater, Inga, Wagener, Rabea, Bernhart, Stephan H., Binder, Hans, Doose, Gero, Hoffmann, Steve, Hopp, Lydia, Kretzmer, Helene, Kreuz, Markus, Langenberger, David, Loeffler, Markus, Rosolowski, Maciej, Schlesner, Matthias, Stadler, Peter F., Sungalee, Stephanie, Kratz, Christian P., van Tilburg, Cornelis M., Kramm, Christof M., Fleischhack, Gudrun, Dirksen, Uta, Rutkowski, Stefan, Frhwald, Michael, von Hoff, Katja, Wolf, Stephan, Klingebiel, Thomas, Koscielniak, Ewa, Koster, Jan, Resnick, Adam C., Zhang, Jinghui, Liu, Yanling, Zhou, Xin, Waanders, Angela J., Zwijnenburg, Danny A., Raman, Pichai, Weber, Ursula D., Northcott, Paul A., Pajtler, Kristian W., Kool, Marcel, Piro, Rosario M., Korbel, Jan O., Jones, David T. W., Chavez, Lukas, and Pfister, Stefan M.

Subjects
Childhood cancer -- Genetic aspects, Cancer research, Gene mutation -- Health aspects, Genomics -- Research, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Pan-cancer analyses that examine commonalities and differences among various cancer types have emerged as a powerful way to obtain novel insights into cancer biology. Here we present a comprehensive analysis of genetic alterations in a pan-cancer cohort including 961 tumours from children, adolescents, and young adults, comprising 24 distinct molecular types of cancer. Using a standardized workflow, we identified marked differences in terms of mutation frequency and significantly mutated genes in comparison to previously analysed adult cancers. Genetic alterations in 149 putative cancer driver genes separate the tumours into two classes: small mutation and structural/copy-number variant (correlating with germline variants). Structural variants, hyperdiploidy, and chromothripsis are linked to TP53 mutation status and mutational signatures. Our data suggest that 78% of the children in this cohort carry an unambiguous predisposing germline variant and that nearly 50% of paediatric neoplasms harbour a potentially druggable event, which is highly relevant for the design of future clinical trials., Author(s): Susanne N. Grbner [1, 2, 3]; Barbara C. Worst [1, 2, 3, 4]; Joachim Weischenfeldt [5, 6]; Ivo Buchhalter [7]; Kortine Kleinheinz [7]; Vasilisa A. Rudneva [5, 8]; Pascal [...]

Published
2018
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16. EpiDiverse Toolkit: a pipeline suite for the analysis of bisulfite sequencing data in ecological plant epigenetics

Author

Nunn, Adam, Can, Sultan Nilay, Otto, Christian, Fasold, Mario, Rodríguez, Bárbara Díez, Fernández-Pozo, Noé, Rensing, Stefan A, Stadler, Peter F, and Langenberger, David

Subjects
Bioinformatics, Epigenetics, Bisulfite Sequencing
Abstract

The expanding scope and scale of next generation sequencing experiments in ecological plant epigenetics brings new challenges for computational analysis. Existing tools built for model data may not address the needs of users looking to apply these techniques to non-model species, particularly on a population or community level. Here we present a toolkit suitable for plant ecologists working with whole genome bisulfite sequencing; it includes pipelines for mapping, the calling of methylation values and differential methylation between groups, epigenome-wide association studies, and a novel implementation for both variant calling and discriminating between genetic and epigenetic variation.

Published
2021

19. The landscape of genomic alterations across childhood cancers

Author

Gröbner, Susanne N., Worst, Barbara C., Weischenfeldt, Joachim, Buchhalter, Ivo, Kleinheinz, Kortine, Rudneva, Vasilisa A., Johann, Pascal D., Balasubramanian, Gnana Prakash, Segura-Wang, Maia, Brabetz, Sebastian, Bender, Sebastian, Hutter, Barbara, Sturm, Dominik, Pfaff, Elke, Hübschmann, Daniel, Zipprich, Gideon, Heinold, Michael, Eils, Jürgen, Lawerenz, Christian, Erkek, Serap, Lambo, Sander, Waszak, Sebastian, Blattmann, Claudia, Borkhardt, Arndt, Kuhlen, Michaela, Eggert, Angelika, Fulda, Simone, Gessler, Manfred, Wegert, Jenny, Kappler, Roland, Baumhoer, Daniel, Burdach, Stefan, Kirschner-Schwabe, Renate, Kontny, Udo, Kulozik, Andreas E., Lohmann, Dietmar, Hettmer, Simone, Eckert, Cornelia, Bielack, Stefan, Nathrath, Michaela, Niemeyer, Charlotte, Richter, Günther H., Schulte, Johannes, Siebert, Reiner, Westermann, Frank, Molenaar, Jan J., Vassal, Gilles, Witt, Hendrik, Lichter, Peter, Weber, Ursula, Eils, Roland, Korshunov, Andrey, Witt, Olaf, Pfister, Stefan, Reifenberger, Guido, Felsberg, Jörg, von Kalle, Christof, Schmidt, Manfred, Bartholomä, Cynthia, Taylor, Michael, Jones, David, Jäger, Natalie, Korbel, Jan, Stütz, Adrian, Rausch, Tobias, Radlwimmer, Bernhard, Yaspo, Marie-Laure, Lehrach, Hans, Warnatz, Hans-Jörg, Landgraf, Pablo, Brors, Benedikt, Zapatka, Marc, Wagner, Susanne, Haake, Andrea, Richter, Julia, Richter, Gesine, Lawerenz, Chris, Kerssemakers, Jules, Jaeger-Schmidt, Christina, Scholz, Ingrid, Bergmann, Anke K., Borst, Christoph, Burkhardt, Birgit, Claviez, Alexander, Dreyling, Martin, Eberth, Sonja, Einsele, Hermann, Frickhofen, Norbert, Haas, Siegfried, Hansmann, Martin-Leo, Karsch, Dennis, Kneba, Michael, Lisfeld, Jasmin, Mantovani-Löffler, Luisa, Rohde, Marius, Ott, German, Stadler, Christina, Staib, Peter, Stilgenbauer, Stephan, Trümper, Lorenz, Zenz, Thorsten, Kube, Dieter, Küppers, Ralf, Weniger, Marc, Hummel, Michael, Klapper, Wolfram, Kostezka, Ulrike, Lenze, Dido, Möller, Peter, Rosenwald, Andreas, Szczepanowski, Monika, Ammerpohl, Ole, Aukema, Sietse M., Binder, Vera, Hoell, Jessica I., Leich, Ellen, López, Cristina, Nagel, Inga, Pischimariov, Jordan, Rosenstiel, Philip, Schilhabel, Markus, Schreiber, Stefan, Vater, Inga, Wagener, Rabea, Bernhart, Stephan H., Binder, Hans, Doose, Gero, Hoffmann, Steve, Hopp, Lydia, Kretzmer, Helene, Kreuz, Markus, Langenberger, David, Loeffler, Markus, Rosolowski, Maciej, Schlesner, Matthias, Stadler, Peter F., Sungalee, Stephanie, Kratz, Christian P., van Tilburg, Cornelis M., Kramm, Christof M., Fleischhack, Gudrun, Dirksen, Uta, Rutkowski, Stefan, Frühwald, Michael, von Hoff, Katja, Wolf, Stephan, Klingebiel, Thomas, Koscielniak, Ewa, Koster, Jan, Resnick, Adam C., Zhang, Jinghui, Liu, Yanling, Zhou, Xin, Waanders, Angela J., Zwijnenburg, Danny A., Raman, Pichai, Weber, Ursula D., Northcott, Paul A., Pajtler, Kristian W., Kool, Marcel, Piro, Rosario M., Korbel, Jan O., Jones, David T. W., Chavez, Lukas, Pfister, Stefan M., Other departments, CCA - Cancer biology and immunology, AGEM - Amsterdam Gastroenterology Endocrinology Metabolism, and Oncogenomics

Subjects
0301 basic medicine, Adult, Mutation rate, Mutation/genetics, Adolescent, DNA Copy Number Variations, Medizin, Biology, DNA Copy Number Variations/genetics, Germ-Line Mutation/genetics, Germline, Cohort Studies, 03 medical and health sciences, Young Adult, Germline mutation, Neoplasms/classification, Mutation Rate, Neoplasms, medicine, Humans, Genetic Predisposition to Disease, Molecular Targeted Therapy, ddc:610, Mutation frequency, Child, Germ-Line Mutation, Genetics, Chromothripsis, Multidisciplinary, Genome, Human, Genetic Predisposition to Disease/genetics, Cancer, Genomics, medicine.disease, Diploidy, Human genetics, 3. Good health, ddc, 030104 developmental biology, Mutation (genetic algorithm), Mutation, Genome, Human/genetics, Tumor Suppressor Protein p53/genetics, Tumor Suppressor Protein p53
Abstract

Pan-cancer analyses that examine commonalities and differences among various cancer types have emerged as a powerful way to obtain novel insights into cancer biology. Here we present a comprehensive analysis of genetic alterations in a pan-cancer cohort including 961 tumours from children, adolescents, and young adults, comprising 24 distinct molecular types of cancer. Using a standardized workflow, we identified marked differences in terms of mutation frequency and significantly mutated genes in comparison to previously analysed adult cancers. Genetic alterations in 149 putative cancer driver genes separate the tumours into two classes: small mutation and structural/copy-number variant (correlating with germline variants). Structural variants, hyperdiploidy, and chromothripsis are linked to TP53 mutation status and mutational signatures. Our data suggest that 7–8% of the children in this cohort carry an unambiguous predisposing germline variant and that nearly 50% of paediatric neoplasms harbour a potentially druggable event, which is highly relevant for the design of future clinical trials.

Published
2020

22. MicroRNA or Not MicroRNA?

Author

Langenberger, David, primary, Bartschat, Sebastian, additional, Hertel, Jana, additional, Hoffmann, Steve, additional, Tafer, Hakim, additional, and Stadler, Peter F., additional

Published
2011
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29. The landscape of genomic alterations across childhood cancers

Author

Gröbner, Susanne N., Worst, Barbara C., Bender, Sebastian, Lichter, Peter, Jäger, Natalie, Buchhalter, Ivo, Korbel, Jan, Stütz, Adrian, Rausch, Tobias, Radlwimmer, Bernhard, Yaspo, Marie-Laure, Lehrach, Hans, Warnatz, Hans-Jörg, Hutter, Barbara, Landgraf, Pablo, Borkhardt, Arndt, Brors, Benedikt, Zapatka, Marc, Eils, Roland, Eils, Jürgen, Lawerenz, Christian, Siebert, Reiner, Wagner, Susanne, Sturm, Dominik, Haake, Andrea, Richter, Julia, Richter, Gesine, Lawerenz, Chris, Kerssemakers, Jules, Jaeger-Schmidt, Christina, Scholz, Ingrid, Bergmann, Anke K., Pfaff, Elke, Borst, Christoph, Burkhardt, Birgit, Claviez, Alexander, Dreyling, Martin, Eberth, Sonja, Einsele, Hermann, Frickhofen, Norbert, Haas, Siegfried, Hansmann, Martin-Leo, Karsch, Dennis, Hübschmann, Daniel, Kneba, Michael, Lisfeld, Jasmin, Mantovani-Löffler, Luisa, Rohde, Marius, Ott, German, Stadler, Christina, Staib, Peter, Stilgenbauer, Stephan, Trümper, Lorenz, Zenz, Thorsten, Zipprich, Gideon, Kube, Dieter, Küppers, Ralf, Weniger, Marc, Hummel, Michael, Klapper, Wolfram, Kostezka, Ulrike, Lenze, Dido, Möller, Peter, Rosenwald, Andreas, Heinold, Michael, Szczepanowski, Monika, Ammerpohl, Ole, Aukema, Sietse M., Binder, Vera, Hoell, Jessica I., Leich, Ellen, López, Cristina, Nagel, Inga, Pischimariov, Jordan, Rosenstiel, Philip, Schilhabel, Markus, Schreiber, Stefan, Vater, Inga, Wagener, Rabea, Bernhart, Stephan H., Binder, Hans, Doose, Gero, Hoffmann, Steve, Hopp, Lydia, Erkek, Serap, Kleinheinz, Kortine, Kretzmer, Helene, Kreuz, Markus, Langenberger, David, Loeffler, Markus, Rosolowski, Maciej, Schlesner, Matthias, Stadler, Peter F., Sungalee, Stephanie, Weischenfeldt, Joachim, Lambo, Sander, Waszak, Sebastian, Blattmann, Claudia, Kuhlen, Michaela, Eggert, Angelika, Fulda, Simone, Gessler, Manfred, Wegert, Jenny, Kappler, Roland, Baumhoer, Daniel, Burdach, Stefan, Kirschner-Schwabe, Renate, Kontny, Hans Udo, Kulozik, Andreas E., Lohmann, Dietmar, Hettmer, Simone, Eckert, Cornelia, Bielack, Stefan, Nathrath, Michaela, Niemeyer, Charlotte, Richter, Günther H., Schulte, Johannes, Westermann, Frank, Molenaar, Jan J., Vassal, Gilles, Witt, Hendrik, ICGC PedBrain-Seq Project, ICGC MMML-Seq Project, Rudneva, Vasilisa A., Kratz, Christian P., Witt, Olaf, van Tilburg, Cornelis M., Kramm, Christof M., Fleischhack, Gudrun, Dirksen, Uta, Rutkowski, Stefan, Frühwald, Michael, von Hoff, Katja, Johann, Pascal D., Wolf, Stephan, Klingebiel, Thomas, Koscielniak, Ewa, Koster, Jan, Resnick, Adam C., Zhang, Jinghui, Liu, Yanling, Zhou, Xin, Waanders, Angela J., Balasubramanian, Gnana Prakash, Zwijnenburg, Danny A., Raman, Pichai, Weber, Ursula D., Northcott, Paul A., Pajtler, Kristian W., Kool, Marcel, Piro, Rosario M., Korbel, Jan O., Segura-Wang, Maia, Jones, David T. W., Chavez, Lukas, Pfister, Stefan M., Weber, Ursula, Korshunov, Andrey, Brabetz, Sebastian, Pfister, Stefan, Reifenberger, Guido, Felsberg, Jörg, von Kalle, Christof, Schmidt, Manfred, Bartholomä, Cynthia, Taylor, Michael, and Jones, David

Published
2018

30. TargetSpy: a supervised machine learning approach for microRNA target prediction

Author

Langenberger David, Hackenberg Michael, Sturm Martin, and Frishman Dmitrij

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background Virtually all currently available microRNA target site prediction algorithms require the presence of a (conserved) seed match to the 5' end of the microRNA. Recently however, it has been shown that this requirement might be too stringent, leading to a substantial number of missed target sites. Results We developed TargetSpy, a novel computational approach for predicting target sites regardless of the presence of a seed match. It is based on machine learning and automatic feature selection using a wide spectrum of compositional, structural, and base pairing features covering current biological knowledge. Our model does not rely on evolutionary conservation, which allows the detection of species-specific interactions and makes TargetSpy suitable for analyzing unconserved genomic sequences. In order to allow for an unbiased comparison of TargetSpy to other methods, we classified all algorithms into three groups: I) no seed match requirement, II) seed match requirement, and III) conserved seed match requirement. TargetSpy predictions for classes II and III are generated by appropriate postfiltering. On a human dataset revealing fold-change in protein production for five selected microRNAs our method shows superior performance in all classes. In Drosophila melanogaster not only our class II and III predictions are on par with other algorithms, but notably the class I (no-seed) predictions are just marginally less accurate. We estimate that TargetSpy predicts between 26 and 112 functional target sites without a seed match per microRNA that are missed by all other currently available algorithms. Conclusion Only a few algorithms can predict target sites without demanding a seed match and TargetSpy demonstrates a substantial improvement in prediction accuracy in that class. Furthermore, when conservation and the presence of a seed match are required, the performance is comparable with state-of-the-art algorithms. TargetSpy was trained on mouse and performs well in human and drosophila, suggesting that it may be applicable to a broad range of species. Moreover, we have demonstrated that the application of machine learning techniques in combination with upcoming deep sequencing data results in a powerful microRNA target site prediction tool http://www.targetspy.org.

Published
2010
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32. High-throughput sequencing and small non-coding RNAs

Author

Langenberger, David, Stadler, Peter F., Nieselt, Kay, and Universität Leipzig

Subjects
High-throughput sequencing, short ncRNA, ddc:500
Abstract

In this thesis the processing mechanisms of short non-coding RNAs (ncRNAs) is investigated by using data generated by the current method of high-throughput sequencing (HTS). The recently adapted short RNA-seq protocol allows the sequencing of RNA fragments of microRNA-like length (∼18-28nt). Thus, after mapping the data back to a reference genome, it is possible to not only measure, but also visualize the expression of all ncRNAs that are processed to fragments of this specific length. Short RNA-seq data was used to show that a highly abundant class of small RNAs, called microRNA-offset-RNAs (moRNAs), which was formerly detected in a basal chordate, is also produced from human microRNA precursors. To simplify the search, the blockbuster tool that automatically recognizes blocks of reads to detect specific expression patterns was developed. By using blockbuster, blocks from moRNAs were detected directly next to the miR or miR* blocks and could thus easily be registered in an automated way. When further investigating the short RNA-seq data it was realized that not only microRNAs give rise to short ∼22nt long RNA pieces, but also almost all other classes of ncRNAs, like tRNAs, snoRNAs, snRNAs, rRNAs, Y-RNAs, or vault RNAs. The formed read patterns that arise after mapping these RNAs back to a reference genome seem to reflect the processing of each class and are thus specific for the RNA transcripts of which they are derived from. The potential of this patterns in classification and identification of non-coding RNAs was explored. Using a random forest classifier which was trained on a set of characteristic features of the individual ncRNA classes, it was possible to distinguish three types of ncRNAs, namely microRNAs, tRNAs, and snoRNAs. To make the classification available to the research community, the free web service ‘DARIO’ that allows to study short read data from small RNA-seq experiments was developed. The classification has shown that read patterns are specific for different classes of ncRNAs. To make use of this feature, the tool deepBlockAlign was developed. deepBlockAlign introduces a two-step approach to align read patterns with the aim of quickly identifying RNAs that share similar processing footprints. In order to find possible exceptions to the well-known microRNA maturation by Dicer and to identify additional substrates for Dicer processing the small RNA sequencing data of a Dicer knockdown experiment in MCF-7 cells was re-evaluated. There were several Dicer-independent microRNAs, among them the important tumor supressor mir-663a. It is known that many aspects of the RNA maturation leave traces in RNA sequencing data in the form of mismatches from the reference genome. It is possible to recover many well- known modified sites in tRNAs, providing evidence that modified nucleotides are a pervasive phenomenon in these data sets.

Published
2013

35. High-throughput sequencing and small non-coding RNAs

Author

Stadler, Peter F., Nieselt, Kay, Universität Leipzig, Langenberger, David, Stadler, Peter F., Nieselt, Kay, Universität Leipzig, and Langenberger, David

Abstract

In this thesis the processing mechanisms of short non-coding RNAs (ncRNAs) is investigated by using data generated by the current method of high-throughput sequencing (HTS). The recently adapted short RNA-seq protocol allows the sequencing of RNA fragments of microRNA-like length (∼18-28nt). Thus, after mapping the data back to a reference genome, it is possible to not only measure, but also visualize the expression of all ncRNAs that are processed to fragments of this specific length. Short RNA-seq data was used to show that a highly abundant class of small RNAs, called microRNA-offset-RNAs (moRNAs), which was formerly detected in a basal chordate, is also produced from human microRNA precursors. To simplify the search, the blockbuster tool that automatically recognizes blocks of reads to detect specific expression patterns was developed. By using blockbuster, blocks from moRNAs were detected directly next to the miR or miR* blocks and could thus easily be registered in an automated way. When further investigating the short RNA-seq data it was realized that not only microRNAs give rise to short ∼22nt long RNA pieces, but also almost all other classes of ncRNAs, like tRNAs, snoRNAs, snRNAs, rRNAs, Y-RNAs, or vault RNAs. The formed read patterns that arise after mapping these RNAs back to a reference genome seem to reflect the processing of each class and are thus specific for the RNA transcripts of which they are derived from. The potential of this patterns in classification and identification of non-coding RNAs was explored. Using a random forest classifier which was trained on a set of characteristic features of the individual ncRNA classes, it was possible to distinguish three types of ncRNAs, namely microRNAs, tRNAs, and snoRNAs. To make the classification available to the research community, the free web service ‘DARIO’ that allows to study short read data from small RNA-seq experiments was developed. The classification has shown that read patterns are specific

Published
2013

36. High-throughput sequencing and small non-coding RNAs

Author

Nieselt, Kay, Universität Leipzig, Langenberger, David, Nieselt, Kay, Universität Leipzig, and Langenberger, David

Abstract

In this thesis the processing mechanisms of short non-coding RNAs (ncRNAs) is investigated by using data generated by the current method of high-throughput sequencing (HTS). The recently adapted short RNA-seq protocol allows the sequencing of RNA fragments of microRNA-like length (∼18-28nt). Thus, after mapping the data back to a reference genome, it is possible to not only measure, but also visualize the expression of all ncRNAs that are processed to fragments of this specific length. Short RNA-seq data was used to show that a highly abundant class of small RNAs, called microRNA-offset-RNAs (moRNAs), which was formerly detected in a basal chordate, is also produced from human microRNA precursors. To simplify the search, the blockbuster tool that automatically recognizes blocks of reads to detect specific expression patterns was developed. By using blockbuster, blocks from moRNAs were detected directly next to the miR or miR* blocks and could thus easily be registered in an automated way. When further investigating the short RNA-seq data it was realized that not only microRNAs give rise to short ∼22nt long RNA pieces, but also almost all other classes of ncRNAs, like tRNAs, snoRNAs, snRNAs, rRNAs, Y-RNAs, or vault RNAs. The formed read patterns that arise after mapping these RNAs back to a reference genome seem to reflect the processing of each class and are thus specific for the RNA transcripts of which they are derived from. The potential of this patterns in classification and identification of non-coding RNAs was explored. Using a random forest classifier which was trained on a set of characteristic features of the individual ncRNA classes, it was possible to distinguish three types of ncRNAs, namely microRNAs, tRNAs, and snoRNAs. To make the classification available to the research community, the free web service ‘DARIO’ that allows to study short read data from small RNA-seq experiments was developed. The classification has shown that read patterns are specific

Published
2013

37. In-Depth miRNA Profiling Of Germinal Center Derived B-Cell Lymphomas By Next Generation Sequencing: A Report From The German Icgc-Mmml-Seq Project

Author

Hoell, Jessica I, primary, Hezaveh, Kebria, additional, Bernhart, Stephan, additional, Hoffmann, Steve, additional, Langenberger, David, additional, Schlesner, Matthias, additional, Stadler, Peter, additional, Binder, Vera, additional, Lenze, Dido, additional, Siebert, Reiner, additional, Hummel, Michael, additional, and Borkhardt, Arndt, additional

Published
2013
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39. Multi-Platform Next-Generation Sequencing of the Domestic Turkey (Meleagris gallopavo): Genome Assembly and Analysis

Author

Dalloul, Rami A., Long, Julie A., Zimin, Aleksey V., Aslam, Luqman, Beal, Kathryn, Blomberg, Le Ann, Bouffard, Pascal, Burt, David W., Crasta, Oswald, Crooijmans, Richard P. M. A., Cooper, Kristal, Coulombe, Roger A., De, Supriyo, Delany, Mary E., Dodgson, Jerry B., Dong, Jennifer J., Evans, Clive, Frederickson, Karin M., Flicek, Paul, Florea, Liliana, Folkerts, Otto, Groenen, Martien A. M., Harkins, Tim T., Herrero, Javier, Hoffmann, Steve, Megens, Hendrik-Jan, Jiang, Andrew, de Jong, Pieter, Kaiser, Pete, Kim, Heebal, Kim, Kyu-Won, Kim, Sungwon, Langenberger, David, Lee, Mi-Kyung, Lee, Taeheon, Mane, Shrinivasrao P., Marcais, Guillaume, Marz, Manja, McElroy, Audrey P., Modise, Thero, Nefedov, Mikhail, Notredame, Cédric, Paton, Ian R., Payne, William S., Pertea, Geo, Prickett, Dennis, Puiu, Daniela, Qioa, Dan, Raineri, Emanuele, Ruffier, Magali, Salzberg, Steven L., Schatz, Michael C., Scheuring, Chantel, Schmidt, Carl J., Schroeder, Steven, Searle, Stephen M. J., Smith, Edward J., Smith, Jacqueline, Sonstegard, Tad S., Stadler, Peter F., Tafer, Hakim, Tu, Zhijian Jake, Van Tassell, Curtis P., Vilella, Albert J., Williams, Kelly P., Yorke, James A., Zhang, Liqing, Zhang, Hong-Bin, Zhang, Xiaojun, Zhang, Yang, Reed, Kent M., Dalloul, Rami A., Long, Julie A., Zimin, Aleksey V., Aslam, Luqman, Beal, Kathryn, Blomberg, Le Ann, Bouffard, Pascal, Burt, David W., Crasta, Oswald, Crooijmans, Richard P. M. A., Cooper, Kristal, Coulombe, Roger A., De, Supriyo, Delany, Mary E., Dodgson, Jerry B., Dong, Jennifer J., Evans, Clive, Frederickson, Karin M., Flicek, Paul, Florea, Liliana, Folkerts, Otto, Groenen, Martien A. M., Harkins, Tim T., Herrero, Javier, Hoffmann, Steve, Megens, Hendrik-Jan, Jiang, Andrew, de Jong, Pieter, Kaiser, Pete, Kim, Heebal, Kim, Kyu-Won, Kim, Sungwon, Langenberger, David, Lee, Mi-Kyung, Lee, Taeheon, Mane, Shrinivasrao P., Marcais, Guillaume, Marz, Manja, McElroy, Audrey P., Modise, Thero, Nefedov, Mikhail, Notredame, Cédric, Paton, Ian R., Payne, William S., Pertea, Geo, Prickett, Dennis, Puiu, Daniela, Qioa, Dan, Raineri, Emanuele, Ruffier, Magali, Salzberg, Steven L., Schatz, Michael C., Scheuring, Chantel, Schmidt, Carl J., Schroeder, Steven, Searle, Stephen M. J., Smith, Edward J., Smith, Jacqueline, Sonstegard, Tad S., Stadler, Peter F., Tafer, Hakim, Tu, Zhijian Jake, Van Tassell, Curtis P., Vilella, Albert J., Williams, Kelly P., Yorke, James A., Zhang, Liqing, Zhang, Hong-Bin, Zhang, Xiaojun, Zhang, Yang, and Reed, Kent M.

Abstract

A synergistic combination of two next-generation sequencing platforms with a detailed comparative BAC physical contig map provided a cost-effective assembly of the genome sequence of the domestic turkey (Meleagris gallopavo). Heterozygosity of the sequenced source genome allowed discovery of more than 600,000 high quality single nucleotide variants. Despite this heterozygosity, the current genome assembly (,1.1 Gb) includes 917 Mb of sequence assigned to specific turkey chromosomes. Annotation identified nearly 16,000 genes, with 15,093 recognized as protein coding and 611 as non-coding RNA genes. Comparative analysis of the turkey, chicken, and zebra finch genomes, and comparing avian to mammalian species, supports the characteristic stability of avian genomes and identifies genes unique to the avian lineage. Clear differences are seen in number and variety of genes of the avian immune system where expansions and novel genes are less frequent than examples of gene loss. The turkey genome sequence provides resources to further understand the evolution of vertebrate genomes and genetic variation underlying economically important quantitative traits in poultry. This integrated approach may be a model for providing both gene and chromosome level assemblies of other species with agricultural, ecological, and evolutionary interest.

Published
2010
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40. Multi-Platform Next-Generation Sequencing of the Domestic Turkey (Meleagris gallopavo): Genome Assembly and Analysis

Author

Animal and Poultry Sciences, Biochemistry, Computer Science, Fralin Life Sciences Institute, Dalloul, Rami A., Long, Julie A., Zimin, Aleksey V., Aslam, Luqman, Beal, Kathryn, Blomberg, Le Ann, Bouffard, Pascal, Burt, David W., Crasta, Oswald, Crooijmans, Richard P. M. A., Cooper, Kristal, Coulombe, Roger A., De, Supriyo, Delany, Mary E., Dodgson, Jerry B., Dong, Jennifer J., Evans, Clive, Frederickson, Karin M., Flicek, Paul, Florea, Liliana, Folkerts, Otto, Groenen, Martien A. M., Harkins, Tim T., Herrero, Javier, Hoffmann, Steve, Megens, Hendrik-Jan, Jiang, Andrew, de Jong, Pieter, Kaiser, Pete, Kim, Heebal, Kim, Kyu-Won, Kim, Sungwon, Langenberger, David, Lee, Mi-Kyung, Lee, Taeheon, Mane, Shrinivasrao P., Marcais, Guillaume, Marz, Manja, McElroy, Audrey P., Modise, Thero, Nefedov, Mikhail, Notredame, Cédric, Paton, Ian R., Payne, William S., Pertea, Geo, Prickett, Dennis, Puiu, Daniela, Qioa, Dan, Raineri, Emanuele, Ruffier, Magali, Salzberg, Steven L., Schatz, Michael C., Scheuring, Chantel, Schmidt, Carl J., Schroeder, Steven, Searle, Stephen M. J., Smith, Edward J., Smith, Jacqueline, Sonstegard, Tad S., Stadler, Peter F., Tafer, Hakim, Tu, Zhijian Jake, Van Tassell, Curtis P., Vilella, Albert J., Williams, Kelly P., Yorke, James A., Zhang, Liqing, Zhang, Hong-Bin, Zhang, Xiaojun, Zhang, Yang, Reed, Kent M., Animal and Poultry Sciences, Biochemistry, Computer Science, Fralin Life Sciences Institute, Dalloul, Rami A., Long, Julie A., Zimin, Aleksey V., Aslam, Luqman, Beal, Kathryn, Blomberg, Le Ann, Bouffard, Pascal, Burt, David W., Crasta, Oswald, Crooijmans, Richard P. M. A., Cooper, Kristal, Coulombe, Roger A., De, Supriyo, Delany, Mary E., Dodgson, Jerry B., Dong, Jennifer J., Evans, Clive, Frederickson, Karin M., Flicek, Paul, Florea, Liliana, Folkerts, Otto, Groenen, Martien A. M., Harkins, Tim T., Herrero, Javier, Hoffmann, Steve, Megens, Hendrik-Jan, Jiang, Andrew, de Jong, Pieter, Kaiser, Pete, Kim, Heebal, Kim, Kyu-Won, Kim, Sungwon, Langenberger, David, Lee, Mi-Kyung, Lee, Taeheon, Mane, Shrinivasrao P., Marcais, Guillaume, Marz, Manja, McElroy, Audrey P., Modise, Thero, Nefedov, Mikhail, Notredame, Cédric, Paton, Ian R., Payne, William S., Pertea, Geo, Prickett, Dennis, Puiu, Daniela, Qioa, Dan, Raineri, Emanuele, Ruffier, Magali, Salzberg, Steven L., Schatz, Michael C., Scheuring, Chantel, Schmidt, Carl J., Schroeder, Steven, Searle, Stephen M. J., Smith, Edward J., Smith, Jacqueline, Sonstegard, Tad S., Stadler, Peter F., Tafer, Hakim, Tu, Zhijian Jake, Van Tassell, Curtis P., Vilella, Albert J., Williams, Kelly P., Yorke, James A., Zhang, Liqing, Zhang, Hong-Bin, Zhang, Xiaojun, Zhang, Yang, and Reed, Kent M.

Abstract

A synergistic combination of two next-generation sequencing platforms with a detailed comparative BAC physical contig map provided a cost-effective assembly of the genome sequence of the domestic turkey (Meleagris gallopavo). Heterozygosity of the sequenced source genome allowed discovery of more than 600,000 high quality single nucleotide variants. Despite this heterozygosity, the current genome assembly (,1.1 Gb) includes 917 Mb of sequence assigned to specific turkey chromosomes. Annotation identified nearly 16,000 genes, with 15,093 recognized as protein coding and 611 as non-coding RNA genes. Comparative analysis of the turkey, chicken, and zebra finch genomes, and comparing avian to mammalian species, supports the characteristic stability of avian genomes and identifies genes unique to the avian lineage. Clear differences are seen in number and variety of genes of the avian immune system where expansions and novel genes are less frequent than examples of gene loss. The turkey genome sequence provides resources to further understand the evolution of vertebrate genomes and genetic variation underlying economically important quantitative traits in poultry. This integrated approach may be a model for providing both gene and chromosome level assemblies of other species with agricultural, ecological, and evolutionary interest.

Published
2010

41. Alu Elements in ANRIL Non-Coding RNA at Chromosome 9p21 Modulate Atherogenic Cell Functions through Trans-Regulation of Gene Networks

Author

Holdt, Lesca M., primary, Hoffmann, Steve, additional, Sass, Kristina, additional, Langenberger, David, additional, Scholz, Markus, additional, Krohn, Knut, additional, Finstermeier, Knut, additional, Stahringer, Anika, additional, Wilfert, Wolfgang, additional, Beutner, Frank, additional, Gielen, Stephan, additional, Schuler, Gerhard, additional, Gäbel, Gabor, additional, Bergert, Hendrik, additional, Bechmann, Ingo, additional, Stadler, Peter F., additional, Thiery, Joachim, additional, and Teupser, Daniel, additional

Published
2013
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42. Mapping the RNA-Seq trash bin

Author

Doose, Gero, primary, Alexis, Maria, additional, Kirsch, Rebecca, additional, Findeiß, Sven, additional, Langenberger, David, additional, Machné, Rainer, additional, Mörl, Mario, additional, Hoffmann, Steve, additional, and Stadler, Peter F., additional

Published
2013
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44. Computational Prediction of MicroRNA Genes.

Author

Hertel, Jana, Langenberger, David, and Stadler, Peter F.

Abstract

The computational identification of novel microRNA (miRNA) genes is a challenging task in bioinformatics. Massive amounts of data describing unknown functional RNA transcripts have to be analyzed for putative miRNA candidates with automated computational pipelines. Beyond those miRNAs that meet the classical definition, high-throughput sequencing techniques have revealed additional miRNA-like molecules that are derived by alternative biogenesis pathways. Exhaustive bioinformatics analyses on such data involve statistical issues as well as precise sequence and structure inspection not only of the functional mature part but also of the whole precursor sequence of the putative miRNA. Apart from a considerable amount of species-specific miRNAs, the majority of all those genes are conserved at least among closely related organisms. Some miRNAs, however, can be traced back to very early points in the evolution of eukaryotic species. Thus, the investigation of the conservation of newly found miRNA candidates comprises an important step in the computational annotation of miRNAs. Topics covered in this chapter include a review on the obvious problem of miRNA annotation and family definition, recommended pipelines of computational miRNA annotation or detection, and an overview of current computer tools for the prediction of miRNAs and their limitations. The chapter closes discussing how those bioinformatic approaches address the problem of faithful miRNA prediction and correct annotation. [ABSTRACT FROM AUTHOR]

Published
2014
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47. Multi-Platform Next-Generation Sequencing of the Domestic Turkey (Meleagris gallopavo): Genome Assembly and Analysis

Author

Dalloul, Rami A., primary, Long, Julie A., additional, Zimin, Aleksey V., additional, Aslam, Luqman, additional, Beal, Kathryn, additional, Ann Blomberg, Le, additional, Bouffard, Pascal, additional, Burt, David W., additional, Crasta, Oswald, additional, Crooijmans, Richard P. M. A., additional, Cooper, Kristal, additional, Coulombe, Roger A., additional, De, Supriyo, additional, Delany, Mary E., additional, Dodgson, Jerry B., additional, Dong, Jennifer J., additional, Evans, Clive, additional, Frederickson, Karin M., additional, Flicek, Paul, additional, Florea, Liliana, additional, Folkerts, Otto, additional, Groenen, Martien A. M., additional, Harkins, Tim T., additional, Herrero, Javier, additional, Hoffmann, Steve, additional, Megens, Hendrik-Jan, additional, Jiang, Andrew, additional, de Jong, Pieter, additional, Kaiser, Pete, additional, Kim, Heebal, additional, Kim, Kyu-Won, additional, Kim, Sungwon, additional, Langenberger, David, additional, Lee, Mi-Kyung, additional, Lee, Taeheon, additional, Mane, Shrinivasrao, additional, Marcais, Guillaume, additional, Marz, Manja, additional, McElroy, Audrey P., additional, Modise, Thero, additional, Nefedov, Mikhail, additional, Notredame, Cédric, additional, Paton, Ian R., additional, Payne, William S., additional, Pertea, Geo, additional, Prickett, Dennis, additional, Puiu, Daniela, additional, Qioa, Dan, additional, Raineri, Emanuele, additional, Ruffier, Magali, additional, Salzberg, Steven L., additional, Schatz, Michael C., additional, Scheuring, Chantel, additional, Schmidt, Carl J., additional, Schroeder, Steven, additional, Searle, Stephen M. J., additional, Smith, Edward J., additional, Smith, Jacqueline, additional, Sonstegard, Tad S., additional, Stadler, Peter F., additional, Tafer, Hakim, additional, Tu, Zhijian (Jake), additional, Van Tassell, Curtis P., additional, Vilella, Albert J., additional, Williams, Kelly P., additional, Yorke, James A., additional, Zhang, Liqing, additional, Zhang, Hong-Bin, additional, Zhang, Xiaojun, additional, Zhang, Yang, additional, and Reed, Kent M., additional

Published
2010
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50. Alu Elements in ANRIL Non-Coding RNA at Chromosome 9p21 Modulate Atherogenic Cell Functions through Trans-Regulation of Gene Networks.

Author

Holdt, Lesca M., Hoffmann, Steve, Sass, Kristina, Langenberger, David, Scholz, Markus, Krohn, Knut, Finstermeier, Knut, Stahringer, Anika, Wilfert, Wolfgang, Beutner, Frank, Gielen, Stephan, Schuler, Gerhard, Gäbel, Gabor, Bergert, Hendrik, Bechmann, Ingo, Stadler, Peter F., Thiery, Joachim, and Teupser, Daniel

Subjects
CHROMOSOMES, ATHEROSCLEROSIS, CORONARY disease, EPIGENESIS, CELL adhesion
Abstract

The chromosome 9p21 (Chr9p21) locus of coronary artery disease has been identified in the first surge of genome-wide association and is the strongest genetic factor of atherosclerosis known today. Chr9p21 encodes the long non-coding RNA (ncRNA) antisense non-coding RNA in the INK4 locus (ANRIL). ANRIL expression is associated with the Chr9p21 genotype and correlated with atherosclerosis severity. Here, we report on the molecular mechanisms through which ANRIL regulates target-genes in trans, leading to increased cell proliferation, increased cell adhesion and decreased apoptosis, which are all essential mechanisms of atherogenesis. Importantly, trans-regulation was dependent on Alu motifs, which marked the promoters of ANRIL target genes and were mirrored in ANRIL RNA transcripts. ANRIL bound Polycomb group proteins that were highly enriched in the proximity of Alu motifs across the genome and were recruited to promoters of target genes upon ANRIL over-expression. The functional relevance of Alu motifs in ANRIL was confirmed by deletion and mutagenesis, reversing trans-regulation and atherogenic cell functions. ANRIL-regulated networks were confirmed in 2280 individuals with and without coronary artery disease and functionally validated in primary cells from patients carrying the Chr9p21 risk allele. Our study provides a molecular mechanism for pro-atherogenic effects of ANRIL at Chr9p21 and suggests a novel role for Alu elements in epigenetic gene regulation by long ncRNAs. [ABSTRACT FROM AUTHOR]

Published
2013
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