27 results on '"Jayson Harshbarger"'
Search Results
2. FANTOM enters 20th year: expansion of transcriptomic atlases and functional annotation of non-coding RNAs.
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Imad Abugessaisa, Jordan A. Ramilowski, Marina Lizio, Jesicca Severin, Akira Hasegawa, Jayson Harshbarger, Atsushi Kondo, Shuhei Noguchi, Chi Wai Yip, Jasmine Li Ching Ooi, Michihira Tagami, Fumi Hori, Saumya Agrawal, Chung-Chau Hon, Mélissa Cardon, Shuya Ikeda, Hiromasa Ono, Hidemasa Bono, Masaki Kato, Kosuke Hashimoto, Alessandro Bonetti, Norio Kobayashi, Jay W. Shin, Michiel J. L. de Hoon, Yoshihide Hayashizaki, Piero Carninci, Hideya Kawaji, and Takeya Kasukawa
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- 2021
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- View/download PDF
3. Update of the FANTOM web resource: high resolution transcriptome of diverse cell types in mammals.
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Marina Lizio, Jayson Harshbarger, Imad Abugessaisa, Shuei Noguchi, Atsushi Kondo, Jessica Severin, Chris Mungall, David J. Arenillas, Anthony Mathelier, Yulia A. Medvedeva, Andreas Lennartsson, Finn Drabløs, Jordan A. Ramilowski, Owen J. L. Rackham, Julian Gough, Robin Andersson, Albin Sandelin, Hans Ienasescu, Hiromasa Ono, Hidemasa Bono, Yoshihide Hayashizaki, Piero Carninci, Alistair R. R. Forrest, Takeya Kasukawa, and Hideya Kawaji
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- 2017
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4. The BioMart community portal: an innovative alternative to large, centralized data repositories.
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Damian Smedley, Syed Haider, Steffen Durinck, Luca Pandini, Paolo Provero, James E. Allen, Olivier Arnaiz, Mohammad Hamza Awedh, Richard A. Baldock, Giulia Barbiera, Philippe Bardou, Tim Beck, Andrew Blake 0003, Merideth Bonierbale, Anthony J. Brookes, Gabriele Bucci, Iwan Buetti, Sarah W. Burge, Cédric Cabau, Joseph W. Carlson, Claude Chelala, Charalambos Chrysostomou, Davide Cittaro, Olivier Collin, Raul Cordova, Rosalind J. Cutts, Erik Dassi, Alex Di Génova, Anis Djari, Anthony Esposito, Heather Estrella, Eduardo Eyras, Julio Fernandez-Banet, Simon A. Forbes, Robert C. Free, Takatomo Fujisawa, Emanuela Gadaleta, Jose M. Garcia-Manteiga, David M. Goodstein, Kristian A. Gray, José Afonso Guerra-Assunção, Bernard Haggarty, Dongjin Han, Byungwoo Han, Todd W. Harris, Jayson Harshbarger, Robert K. Hastings, Richard D. Hayes, Claire Hoede, Shen Hu, Zhi-Liang Hu, Lucie N. Hutchins, Zhengyan Kan, Hideya Kawaji, Aminah-Olivia Keliet, Arnaud Kerhornou, Sunghoon Kim 0001, Rhoda Kinsella, Christophe Klopp, Lei Kong, Daniel Lawson, Dejan Lazarevic, Ji-Hyun Lee, Thomas Letellier, Chuan-Yun Li, Pietro Liò, Chu-Jun Liu, Jie Luo, Alejandro Maass, Jérôme Mariette, Thomas Maurel, Stefania Merella, Azza Mostafa Mohamed, François Moreews, Nabihoudine Ibouniyamine, Nelson Ndegwa, Céline Noirot, Christian Perez-Llamas, Michael Primig, Alessandro Quattrone, Hadi Quesneville, Davide Rambaldi, James M. Reecy, Michela Riba, Steven Rosanoff, Amna Ali Saddiq, Elisa Salas, Olivier Sallou, Rebecca Shepherd, Reinhard Simon, Linda Sperling, William Spooner, Daniel M. Staines, Delphine Steinbach, Kevin R. Stone, Elia Stupka, Jon W. Teague, Abu Z. Dayem Ullah, Jun Wang 0060, Doreen Ware, Marie Wong-Erasmus, Ken Youens-Clark, Amonida Zadissa, Shi-Jian Zhang, and Arek Kasprzyk
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- 2015
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5. A promoter-level mammalian expression atlas.
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The Fantom Consortium, RIKEN PMII, RIKEN CLST (DGT), Alistair R. R. Forrest, Hideya Kawaji, Michael Rehli, J. Kenneth Baillie, Michiel J. L. de Hoon, Vanja Haberle, Timo Lassmann, Ivan V. Kulakovskiy, Marina Lizio, Masayoshi Itoh, Robin Andersson, Christopher J. Mungall, Terrence F. Meehan, Sebastian Schmeier, Nicolas Bertin, Mette Jørgensen, Emmanuel Dimont, Erik Arner, Christian Schmidl, Ulf Schaefer, Yulia A. Medvedeva, Charles Plessy, Morana Vitezic, Jessica Severin, Colin A. M. Semple, Yuri Ishizu, Robert S. Young, Margherita Francescatto, Intikhab Alam, Davide Albanese, Gabriel M. Altschuler, Takahiro Arakawa, John A. C. Archer, Peter Arner, Magda Babina, Sarah Rennie, Piotr J. Balwierz, Anthony G. Beckhouse, Swati Pradhan-Bhatt, Judith A. Blake, Antje Blumenthal, Beatrice Bodega, Alessandro Bonetti, James Briggs, Frank Brombacher, A. Maxwell Burroughs, Andrea Califano, Carlo V. Cannistraci, Daniel Carbajo, Yun Chen, Marco Chierici, Yari Ciani, Hans Clevers, Emiliano Dalla, Carrie A. Davis, Michael Detmar, Alexander D. Diehl, Taeko Dohi, Finn Drabløs, Albert S. B. Edge, Matthias Edinger, Karl Ekwall, Mitsuhiro Endoh, Hideki Enomoto, Michela Fagiolini, Lynsey Fairbairn, Hai Fang, Mary C. Farach-Carson, Geoffrey J. Faulkner, Alexander V. Favorov, Malcolm E. Fisher, Martin C. Frith, Rie Fujita, Shiro Fukuda, Cesare Furlanello, Masaaki Furuno, Jun-ichi Furusawa, Teunis B. Geijtenbeek, Andrew P. Gibson, Thomas R. Gingeras, Daniel Goldowitz, Julian Gough, Sven Guhl, Reto Guler, Stefano Gustincich, Thomas J. Ha, Masahide Hamaguchi, Mitsuko Hara, Matthias Harbers, Jayson Harshbarger, Akira Hasegawa, Yuki Hasegawa, Takehiro Hashimoto, Meenhard Herlyn, Kelly J. Hitchens, Shannan J. Ho Sui, Oliver M. Hofmann, Ilka Hoof, Fumi Hori, Lukasz Huminiecki, Kei Iida, Tomokatsu Ikawa, Boris R. Jankovic, Hui Jia, Anagha Joshi, Giuseppe Jurman, Bogumil Kaczkowski, Chieko Kai, Kaoru Kaida, Ai Kaiho, Kazuhiro Kajiyama, Mutsumi Kanamori-Katayama, Artem S. Kasianov, Takeya Kasukawa, Shintaro Katayama, Sachi Kato, Shuji Kawaguchi, Hiroshi Kawamoto, Yuki I. Kawamura, Tsugumi Kawashima, Judith S. Kempfle, Tony J. Kenna, Juha Kere, Levon M. Khachigian, Toshio Kitamura, S. Peter Klinken, Alan J. Knox, Miki Kojima, Soichi Kojima, Naoto Kondo, Haruhiko Koseki, Shigeo Koyasu, Sarah Krampitz, Atsutaka Kubosaki, Andrew T. Kwon, Jeroen F. J. Laros, Weonju Lee, Andreas Lennartsson, Kang Li, Berit Lilje, Leonard Lipovich, Alan Mackay-Sim, Ri-ichiroh Manabe, Jessica Cara Mar, Benoit Marchand, Anthony Mathelier, Niklas Mejhert, Alison M. Meynert, Yosuke Mizuno, David A. de Lima Morais, Hiromasa Morikawa, Mitsuru Morimoto, Kazuyo Moro, Efthymios Motakis, Hozumi Motohashi, Christine Mummery, Mitsuyoshi Murata, Sayaka Nagao-Sato, Yutaka Nakachi, Fumio Nakahara, Toshiyuki Nakamura, Yukio Nakamura, Kenichi Nakazato, Erik van Nimwegen, Noriko Ninomiya, Hiromi Nishiyori, Shohei Noma, Tadasuke Nozaki, Soichi Ogishima, Naganari Ohkura, Hiroko Ohmiya, Hiroshi Ohno, Mitsuhiro Ohshima, Mariko Okada-Hatakeyama, Yasushi Okazaki, Valerio Orlando, Dmitry A. Ovchinnikov, Arnab Pain, Robert Passier, Margaret Patrikakis, Helena Persson, Silvano Piazza, James G. D. Prendergast, Owen J. L. Rackham, Jordan A. Ramilowski, Mamoon Rashid, Timothy Ravasi, Patrizia Rizzu, Marco Roncador, Sugata Roy, Morten B. Rye, Eri Saijyo, Antti Sajantila, Akiko Saka, Shimon Sakaguchi, Mizuho Sakai, Hiroki Sato, Hironori Sato, Suzana Savvi, Alka Saxena, Claudio Schneider, Erik A. Schultes, Gundula G. Schulze-Tanzil, Anita Schwegmann, Thierry Sengstag, Guojun Sheng, Hisashi Shimoji, Yishai Shimoni, Jay W. Shin, Christophe Simon, Daisuke Sugiyama, Takaaki Sugiyama, Masanori Suzuki, Naoko Suzuki, Rolf K. Swoboda, Peter A. C. 't Hoen, Michihira Tagami, Naoko Takahashi, Jun Takai, Hiroshi Tanaka, Hideki Tatsukawa, Zuotian Tatum, Mark Thompson 0002, Hiroo Toyoda, Tetsuro Toyoda, Eivind Valen, Marc van de Wetering, Linda M. van den Berg, Roberto Verardo, Dipti Vijayan, Ilya E. Vorontsov, Wyeth W. Wasserman, Shoko Watanabe, Christine A. Wells, Louise N. Winteringham, Ernst Wolvetang, Emily J. Wood, Yoko Yamaguchi, Masayuki Yamamoto, Misako Yoneda, Yohei Yonekura, Shigehiro Yoshida, Susan E. Zabierowski, Peter G. Zhang, Xiaobei Zhao, Silvia Zucchelli, Kim M. Summers, Harukazu Suzuki, Carsten O. Daub, Jun Kawai, Peter Heutink, Winston Hide, Tom C. Freeman, Boris Lenhard, Vladimir B. Bajic, Martin S. Taylor, Vsevolod J. Makeev, Albin Sandelin, David A. Hume, Piero Carninci, and Yoshihide Hayashizaki
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- 2014
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6. FANTOM5 transcriptome catalog of cellular states based on Semantic MediaWiki.
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Imad Abugessaisa, Hisashi Shimoji, Serkan Sahin, Atsushi Kondo, Jayson Harshbarger, Marina Lizio, Yoshihide Hayashizaki, Piero Carninci, Alistair R. R. Forrest, Takeya Kasukawa, and Hideya Kawaji
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- 2016
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7. FANTOM enters 20th year: expansion of transcriptomic atlases and functional annotation of non-coding RNAs
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Imad Abugessaisa, Jordan A Ramilowski, Marina Lizio, Jesicca Severin, Akira Hasegawa, Jayson Harshbarger, Atsushi Kondo, Shuhei Noguchi, Chi Wai Yip, Jasmine Li Ching Ooi, Michihira Tagami, Fumi Hori, Saumya Agrawal, Chung Chau Hon, Melissa Cardon, Shuya Ikeda, Hiromasa Ono, Hidemasa Bono, Masaki Kato, Kosuke Hashimoto, Alessandro Bonetti, Norio Kobayashi, Jay Shin, Michiel de Hoon, Yoshihide Hayashizaki, Piero Carninci, Hideya Kawaji, and Takeya Kasukawa
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AcademicSubjects/SCI00010 ,Computational biology ,Biology ,Genome ,Transcriptome ,Mice ,User-Computer Interface ,Genetics ,Animals ,Humans ,Database Issue ,Promoter Regions, Genetic ,computer.programming_language ,Metadata ,Binding Sites ,Fantom ,Molecular Sequence Annotation ,Fibroblasts ,Chromatin ,Gene expression profiling ,MicroRNAs ,Functional annotation ,Drosophila ,RNA, Long Noncoding ,Mammalian genome ,computer ,Transcription Factors ,Reference genome - Abstract
The Functional ANnoTation Of the Mammalian genome (FANTOM) Consortium has continued to provide extensive resources in the pursuit of understanding the transcriptome, and transcriptional regulation, of mammalian genomes for the last 20 years. To share these resources with the research community, the FANTOM web-interfaces and databases are being regularly updated, enhanced and expanded with new data types. In recent years, the FANTOM Consortium's efforts have been mainly focused on creating new non-coding RNA datasets and resources. The existing FANTOM5 human and mouse miRNA atlas was supplemented with rat, dog, and chicken datasets. The sixth (latest) edition of the FANTOM project was launched to assess the function of human long non-coding RNAs (lncRNAs). From its creation until 2020, FANTOM6 has contributed to the research community a large dataset generated from the knock-down of 285 lncRNAs in human dermal fibroblasts; this is followed with extensive expression profiling and cellular phenotyping. Other updates to the FANTOM resource includes the reprocessing of the miRNA and promoter atlases of human, mouse and chicken with the latest reference genome assemblies. To facilitate the use and accessibility of all above resources we further enhanced FANTOM data viewers and web interfaces. The updated FANTOM web resource is publicly available at https://fantom.gsc.riken.jp/.
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- 2020
8. Automated identification of cell-type–specific genes and alternative promoters
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Michael M. Hoffman, Jayson Harshbarger, and Mickaël Mendez
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Transcriptome ,Cell type ,Lineage (genetic) ,Cluster of differentiation ,Cellular differentiation ,Promoter ,Genomics ,Computational biology ,Biology ,Gene - Abstract
BackgroundIdentifying key transcriptional features, such as genes or transcripts, involved in cellular differentiation remains a challenging problem. Current methods for identifying key transcriptional features predominantly rely on pairwise comparisons among different cell types. These methods also identify long lists of differentially expressed transcriptional features. Combining the results from many such pairwise comparisons to find the transcriptional features specific only to one cell type is not straightforward. Thus, one must have a principled method for amalgamating pairwise cell type comparisons that makes full use of prior knowledge about the developmental relationships between cell types.MethodWe developed Cell Lineage Analysis (CLA), a computational method which identifies transcriptional features with expression patterns that discriminate cell types, incorporating Cell Ontology knowledge on the relationship between different cell types. CLA uses random forest classification with a stratified bootstrap to increase the accuracy of binary classifiers when each cell type have a different number of samples. Regularized random forest results in a classifier that selects few but important transcriptional features. For each cell type pair, CLA runs multiple instances of regularized random forest and reports the transcriptional features consistently selected. CLA not only discriminates individual cell types but can also discriminate lineages of cell types related in the developmental hierarchy.ResultsWe applied CLA to Functional Annotation of the Mammalian Genome 5 (FANTOM5) data and identified discriminative transcription factor and long non-coding RNA(lncRNA) genes for 71 human cell types.With capped analysis of gene expression (CAGE) data, CLA identified individual cell-type–specific alternative promoters for cell surface markers. Compared to random forest with a standard bootstrap approach, CLA’s stratified bootstrap approach improved the accuracy of gene expression classification models for more than 95% of 2060 cell type pairs examined. Applied on 10X Genomics single-cell RNA-seq data for CD14+ monocytes and FCGR3A+ monocytes, CLA selected only 13 discriminative genes. These genes included the top 9 out of 370 significantly differentially expressed genes obtained from conventional differential expression analysis methods.DiscussionOur CLA method combines tools to simplify the interpretation of transcriptome datasets from many cell types. It automates the identification of the most differentially expressed genes for each cell type pairs CLA’s lineage score allows easy identification of the best transcriptional markers for each cell type and lineage in both bulk and single-cell transcriptomic data.AvailabilityCLA is available at https://cla.hoffmanlab.org. We deposited the version of the CLA source with which we ran our experiments at https://doi.org/10.5281/zenodo.3630670. We deposited other analysis code and results at https://doi.org/10.5281/zenodo.5735636.
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- 2021
9. Corrigendum: Functional annotation of human long noncoding RNAs via molecular phenotyping
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Claudio Schneider, Malte Thodberg, Akira Hasegawa, Haruhiko Koseki, Saumya Agrawal, Harukazu Suzuki, Carlo Vittorio Cannistraci, Yulia A. Medvedeva, Bogumil Kaczkowski, Jen Chien Chang, Youtaro Shibayama, Chi Wai Yip, Ivan Antonov, Takahiro Suzuki, Jayson Harshbarger, Mariola Kurowska-Stolarska, Luigi Marchionni, Leonie Roos, Chikashi Terao, Supat Thongjuea, Melissa Cardon, Ferenc Müller, Christopher J. F. Cameron, Hideya Kawaji, Naoto Kondo, Vsevolod J. Makeev, Alessandro Bonetti, Josée Dostie, Reto Guler, Kazuhiro R. Nitta, Shuhei Noguchi, Jasmine Li, Altuna Akalin, Michiel J. L. de Hoon, Nicholas J. Parkinson, Emily Kawabata, Chung-Chau Hon, Albin Sandelin, Tsugumi Kawashima, Callum J.C. Parr, Roberto Verardo, Aditi Kanhere, Roderic Guigó, Ivan V. Kulakovskiy, Igor Ulitsky, Pillay Sanjana, S. Thomas Kelly, Michael M. Hoffman, Yasushi Okazaki, Boris Lenhard, Yari Ciani, Andreas Lennartsson, Vidisha Tripathi, Imad Abugessaisa, Erik Arner, Denis Paquette, Ramil N. Nurtdinov, Robert Young, Chinatsu Yamamoto, Ken Yagi, Jordan A. Ramilowski, Alistair R. R. Forrest, Kayoko Yasuzawa, Aki Minoda, Jessica Severin, Peter Heutink, Norihito Hayatsu, Hiromi Nishiyori, Frank Brombacher, Tsukasa Kouno, Juha Kere, Lusy Handoko, J Kenneth Baillie, Andrew T. Kwon, Howard Y. Chang, Masayoshi Itoh, Yuki Hasegawa, Sakari Kauppinen, Andreas Petri, Ching Ooi, Luca Ducoli, Kosuke Hashimoto, Suzannah C. Szumowski, Tetsuro Hirose, Ryan Cardenas, Patrizia Rizzu, Eddie Luidy Imada, Colin A. Semple, Anton Kratz, Valerio Orlando, Alexander V. Favorov, Martin S. Taylor, Takeya Kasukawa, Joachim Luginbühl, Divya M. Sivaraman, Piero Carninci, Fernando López-Redondo, Hidemasa Bono, Yukihiko Noro, Marina Lizio, Beatrice Borsari, Mitsuyoshi Murata, Juliette Gimenez, Mickaël Mendez, Diego Fernando Sánchez Martinez, Diego Garrido, Michihira Tagami, Manuel Muñoz-Aguirre, Noa Gil, Shiori Maeda, John F. Ouyang, Jeffrey T. Leek, Alexandre Fort, Miki Kojima, Owen J. L. Rackham, Ilya E. Vorontsov, and Jay W. Shin
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Functional annotation ,Genome research ,Genetics ,Computational biology ,Biology ,Corrigendum ,Genetics (clinical) - Published
- 2020
10. Functional annotation of human long noncoding RNAs via molecular phenotyping
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Jayson Harshbarger, Hideya Kawaji, Diego Garrido, Michiel J. L. de Hoon, Tsugumi Kawashima, Lusy Handoko, Masayoshi Itoh, John F. Ouyang, Michihira Tagami, Kosuke Hashimoto, Andreas Petri, Patrizia Rizzu, Christopher J. F. Cameron, Tetsuro Hirose, Marina Lizio, Beatrice Borsari, Robert Young, Vidisha Tripathi, Chung-Chau Hon, Joachim Luginbühl, Ryan Cardenas, Jasmine Li Ching Ooi, Chikashi Terao, Vsevolod J. Makeev, Aki Minoda, Colin A. Semple, Alexander V. Favorov, Yasushi Okazaki, Kazuhiro R. Nitta, Mitsuyoshi Murata, Juha Kere, Harukazu Suzuki, Bogumil Kaczkowski, Fernando López-Redondo, Ivan Antonov, Mickaël Mendez, Diego Fernando Sánchez Martinez, Michael M. Hoffman, Chi Wai Yip, Imad Abugessaisa, Pillay Sanjana, Sakari Kauppinen, Erik Arner, Denis Paquette, Norihito Hayatsu, Ramil N. Nurtdinov, Mariola Kurowska-Stolarska, Luigi Marchionni, Takahiro Suzuki, Claudio Schneider, J Kenneth Baillie, Andrew T. Kwon, Saumya Agrawal, Carlo Vittorio Cannistraci, Roberto Verardo, Suzannah C. Szumowski, Frank Brombacher, Tsukasa Kouno, Boris Lenhard, Noa Gil, Manuel Muñoz-Aguirre, Shiori Maeda, Luca Ducoli, Emily Kawabata, Valerio Orlando, Leonie Roos, Divya M. Sivaraman, Youtaro Shibayama, Supat Thongjuea, Piero Carninci, Kayoko Yasuzawa, Jeffrey T. Leek, Alexandre Fort, Hidemasa Bono, Peter Heutink, Takeya Kasukawa, Alessandro Bonetti, Jen-Chien Chang, Josée Dostie, Naoto Kondo, Ferenc Müller, Nicholas J. Parkinson, Haruhiko Koseki, Malte Thodberg, Callum J.C. Parr, Anton Kratz, Miki Kojima, Reto Guler, Jordan A. Ramilowski, Alistair R. R. Forrest, Owen J. L. Rackham, Igor Ulitsky, Yari Ciani, Howard Y. Chang, Roderic Guigó, Jay W. Shin, Andreas Lennartsson, Ivan V. Kulakovskiy, Jessica Severin, Ilya E. Vorontsov, Melissa Cardon, Ken Yagi, Chinatsu Yamamoto, Yukihiko Noro, Juliette Gimenez, Shuhei Noguchi, Yuki Hasegawa, Eddie Luidy Imada, Martin S. Taylor, Yulia A. Medvedeva, Altuna Akalin, Albin Sandelin, Aditi Kanhere, S. Thomas Kelly, Hiromi Nishiyori, Akira Hasegawa, Wellcome Trust, STEMM - Stem Cells and Metabolism Research Program, Juha Kere / Principal Investigator, Research Programs Unit, University of Helsinki, and HUS Helsinki and Uusimaa Hospital District
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Genome ,Transcriptome ,0302 clinical medicine ,Cell Movement ,Transcription (biology) ,antagonists & inhibitors [RNA, Long Noncoding] ,Gene expression ,cytology [Fibroblasts] ,TRANSCRIPTION ,RNA, Small Interfering ,Genetics (clinical) ,11 Medical and Health Sciences ,GENE-EXPRESSION ,Genetics & Heredity ,0303 health sciences ,Gene knockdown ,318 Medical biotechnology ,KCNQ Potassium Channels ,1184 Genetics, developmental biology, physiology ,physiology [RNA, Long Noncoding] ,Phenotype ,DIFFERENTIATION ,ddc:540 ,RNA, Long Noncoding ,Technology Platforms ,Life Sciences & Biomedicine ,metabolism [Fibroblasts] ,Resource ,Biochemistry & Molecular Biology ,Bioinformatics ,UNIQUE FEATURES ,Cell Growth Processes ,Computational biology ,Biology ,ADULT HUMAN FIBROBLASTS ,03 medical and health sciences ,REVEALS ,Genetics ,genetics [Cell Growth Processes] ,Humans ,Gene ,030304 developmental biology ,REGULATORS ,Science & Technology ,metabolism [KCNQ Potassium Channels] ,Cell growth ,genetics [Cell Movement] ,Molecular Sequence Annotation ,Fibroblasts ,Oligonucleotides, Antisense ,06 Biological Sciences ,Biotechnology & Applied Microbiology ,Cardiovascular and Metabolic Diseases ,PRINCIPLES ,CELLS ,metabolism [RNA, Long Noncoding] ,1182 Biochemistry, cell and molecular biology ,3111 Biomedicine ,TRANSLATION ,030217 neurology & neurosurgery - Abstract
Long noncoding RNAs (lncRNAs) constitute the majority of transcripts in the mammalian genomes, and yet, their functions remain largely unknown. As part of the FANTOM6 project, we systematically knocked down the expression of 285 lncRNAs in human dermal fibroblasts and quantified cellular growth, morphological changes, and transcriptomic responses using Capped Analysis of Gene Expression (CAGE). Antisense oligonucleotides targeting the same lncRNAs exhibited global concordance, and the molecular phenotype, measured by CAGE, recapitulated the observed cellular phenotypes while providing additional insights on the affected genes and pathways. Here, we disseminate the largest-to-date lncRNA knockdown data set with molecular phenotyping (over 1000 CAGE deep-sequencing libraries) for further exploration and highlight functional roles for ZNF213-AS1 and lnc-KHDC3L-2.
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- 2020
11. Functional Annotation of Human Long Non-Coding RNAs via Molecular Phenotyping
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Howard Y. Chang, Manuel Muñoz-Aguirre, Roderic Guigó, Andreas Lennartsson, Chinatsu Yamamoto, Robert Young, Ramil N. Nurtdinov, Jasmine Li Ching Ooi, Christopher J. F. Cameron, Andreas Petri, Valerio Orlando, Tetsuro Hirose, Vidisha Tripathi, Tsugumi Kawashima, Joachim Luginbühl, Ilya E. Vorontsov, Diego Garrido, Jeffrey T. Leek, Alexandre Fort, Ryan Cardenas, Colin A. Semple, Aki Minoda, Takeya Kasukawa, Michiel J. L. de Hoon, Alexander V. Favorov, Peter Heutink, Harukazu Suzuki, Jordan A. Ramilowski, Alistair R. R. Forrest, Michihira Tagami, Imad Abugessaisa, Malte Thodberg, J Kenneth Baillie, Andrew T. Kwon, Juha Kere, Ivan V. Kulakovskiy, Jen-Chien Chang, Yuki Hasegawa, Melissa Cardon, Kazuhiro R. Nitta, John F. Ouyang, Jay W. Shin, Noa Gil, Jessica Severin, Reto Guler, Shiori Maeda, Eddie Luidy Imada, Emily Kawabata, Sakari Kauppinen, Hideya Kawaji, Pillay Sanjana, Miki Kojima, Yulia A. Medvedeva, Igor Ulitsky, Suzannah C. Szumowski, Martin S. Taylor, Michael M. Hoffman, Denis Paquette, Yari Ciani, Yukihiko Noro, S. Thomas Kelly, Mickaël Mendez, Diego Fernando Sánchez Martinez, Lusy Handoko, Jayson Harshbarger, Roberto Verardo, Owen J. L. Rackham, Bogumil Kaczkowski, Ivan Antonov, Frank Brombacher, Akira Hasegawa, Tsukasa Kouno, Fernando López-Redondo, Mariola Kurowska-Stolarska, Luigi Marchionni, Supat Thongjuea, N. Hayatsu, Ken Yagi, Juliette Gimenez, Anton Kratz, Hiromi Nishiyori, Shuhei Noguchi, Kayoko Yasuzawa, Chi Wai Yip, Chung-Chau Hon, Altuna Akalin, Albin Sandelin, Aditi Kanhere, Marina Lizio, Beatrice Borsari, Chikashi Terao, Vsevolod J. Makeev, Luca Ducoli, Alessandro Bonetti, Josée Dostie, Divya M. Sivaraman, Masayoshi Itoh, Piero Carninci, Hidemasa Bono, Erik Arner, Kosuke Hashimoto, Yasushi Okazaki, Patrizia Rizzu, Mitsuyoshi Murata, Callum J.C. Parr, Boris Lenhard, Ferenc Müller, Claudio Schneider, Youtaro Shibayama, Saumya Agrawal, Carlo Vittorio Cannistraci, Leonie Roos, Naoto Kondo, Nicholas J. Parkinson, Haruhiko Koseki, and Takahiro Suzuki
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0303 health sciences ,Gene knockdown ,Cell growth ,Computational biology ,Biology ,Genome ,Phenotype ,Transcriptome ,03 medical and health sciences ,0302 clinical medicine ,Functional annotation ,030220 oncology & carcinogenesis ,Gene expression ,Gene ,030304 developmental biology - Abstract
Long non-coding RNAs (lncRNAs) constitute the majority of transcripts in the mammalian genomes and yet, their functions remain largely unknown. We systematically knockdown 285 lncRNAs expression in human dermal fibroblasts and quantified cellular growth, morphological changes, and transcriptomic responses using Capped Analysis of Gene Expression (CAGE). Antisense oligonucleotides targeting the same lncRNA exhibited global concordance, and the molecular phenotype, measured by CAGE, recapitulated the observed cellular phenotypes while providing additional insights on the affected genes and pathways. Here, we disseminate the largest to-date lncRNA knockdown dataset with molecular phenotyping (over 1,000 CAGE deep-sequencing libraries) for further exploration and highlight functional roles for ZNF213-AS1 and lnc-KHDC3L-2.
- Published
- 2019
- Full Text
- View/download PDF
12. Author Correction: Transcription start site profiling of 15 anatomical regions of the Macaca mulatta central nervous system
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Piero Carninci, Imad Abugessaisa, Ingrid H.C.H.M. Philippens, Timo Lassmann, Luba M. Pardo, Marina Lizio, Jayson Harshbarger, Akira Hasegawa, Mizuho Sakai, Masayoshi Itoh, Margherita Francescatto, Takeya Kasukawa, Peter Heutink, Patrizia Rizzu, Alistair R. R. Forrest, Shoko Watanabe, Yoshihide Hayashizaki, Jessica Severin, Ronald E. Bontrop, and Hideya Kawaji
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Data descriptor ,Statistics and Probability ,Data Descriptor ,TheoryofComputation_COMPUTATIONBYABSTRACTDEVICES ,Computer science ,MEDLINE ,Library and Information Sciences ,computer.software_genre ,Education ,Profiling (information science) ,lcsh:Science ,Transcriptomics ,business.industry ,Published Erratum ,Regret ,RNA sequencing ,Gene expression profiling ,Computer Science Applications ,ComputingMethodologies_DOCUMENTANDTEXTPROCESSING ,lcsh:Q ,Artificial intelligence ,ddc:500 ,Gene expression ,Statistics, Probability and Uncertainty ,business ,computer ,Natural language processing ,Information Systems - Abstract
Rhesus macaque was the second non-human primate whose genome has been fully sequenced and is one of the most used model organisms to study human biology and disease, thanks to the close evolutionary relationship between the two species. But compared to human, where several previously unknown RNAs have been uncovered, the macaque transcriptome is less studied. Publicly available RNA expression resources for macaque are limited, even for brain, which is highly relevant to study human cognitive abilities. In an effort to complement those resources, FANTOM5 profiled 15 distinct anatomical regions of the aged macaque central nervous system using Cap Analysis of Gene Expression, a high-resolution, annotation-independent technology that allows monitoring of transcription initiation events with high accuracy. We identified 25,869 CAGE peaks, representing bona fide promoters. For each peak we provide detailed annotation, expanding the landscape of ‘known’ macaque genes, and we show concrete examples on how to use the resulting data. We believe this data represents a useful resource to understand the central nervous system in macaque.
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- 2018
13. Update of the FANTOM web resource: high resolution transcriptome of diverse cell types in mammals
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Jayson Harshbarger, Imad Abugessaisa, Julian Gough, Takeya Kasukawa, Andreas Lennartsson, Hiromasa Ono, Jordan A. Ramilowski, Alistair R. R. Forrest, Atsushi Kondo, Hans-Ioan Ienasescu, Shuei Noguchi, Jessica Severin, David J. Arenillas, Anthony Mathelier, Piero Carninci, Marina Lizio, Hidemasa Bono, Yoshihide Hayashizaki, Yulia A. Medvedeva, Finn Drabløs, Albin Sandelin, Robin Andersson, Hideya Kawaji, Owen J. L. Rackham, and Christopher J. Mungall
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0301 basic medicine ,High resolution ,Genomics ,Biology ,Web Browser ,Bioinformatics ,World Wide Web ,Transcriptome ,Databases ,03 medical and health sciences ,0302 clinical medicine ,Resource (project management) ,Genetic ,Information and Computing Sciences ,Databases, Genetic ,Genetics ,Database Issue ,Animals ,Humans ,Cellular organization ,computer.programming_language ,Mammals ,Gene Expression Profiling ,Fantom ,Computational Biology ,Biological Sciences ,Search Engine ,030104 developmental biology ,Functional annotation ,Generic health relevance ,Web resource ,computer ,Environmental Sciences ,030217 neurology & neurosurgery ,Software ,Developmental Biology - Abstract
Upon the first publication of the fifth iteration of the Functional Annotation of Mammalian Genomes collaborative project, FANTOM5, we gathered a series of primary data and database systems into the FANTOM web resource (http://fantom.gsc.riken.jp) to facilitate researchers to explore transcriptional regulation and cellular states. In the course of the collaboration, primary data and analysis results have been expanded, and functionalities of the database systems enhanced. We believe that our data and web systems are invaluable resources, and we think the scientific community will benefit for this recent update to deepen their understanding of mammalian cellular organization. We introduce the contents of FANTOM5 here, report recent updates in the web resource and provide future perspectives. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/)
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- 2016
14. Monitoring transcription initiation activities in rat and dog
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Marina Lizio, Hideya Kawaji, Abdul Kadir Mukarram, Alistair R. R. Forrest, Shoko Watanabe, Jayson Harshbarger, Yoshihide Hayashizaki, Takeya Kasukawa, Chung-Chau Hon, Masayoshi Itoh, Imad Abugessaisa, Piero Carninci, Akira Hasegawa, Jessica Severin, Timo Lassmann, and Mizuho Ohno
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0301 basic medicine ,Statistics and Probability ,Data Descriptor ,Cell type ,Transcription, Genetic ,ved/biology.organism_classification_rank.species ,Computational biology ,Library and Information Sciences ,Biology ,Education ,Transcriptome ,03 medical and health sciences ,Dogs ,Computational platforms and environments ,Transcription (biology) ,Animals ,Promoter Regions, Genetic ,Transcriptomics ,Model organism ,Gene ,ved/biology ,Mesenchymal stem cell ,Molecular Sequence Annotation ,Gene Annotation ,Cap analysis gene expression ,Rats ,Research data ,Computer Science Applications ,Data processing ,030104 developmental biology ,Transcription Initiation Site ,Statistics, Probability and Uncertainty ,Information Systems - Abstract
The promoter landscape of several non-human model organisms is far from complete. As a part of FANTOM5 data collection, we generated 13 profiles of transcription initiation activities in dog and rat aortic smooth muscle cells, mesenchymal stem cells and hepatocytes by employing CAGE (Cap Analysis of Gene Expression) technology combined with single molecule sequencing. Our analyses show that the CAGE profiles recapitulate known transcription start sites (TSSs) consistently, in addition to uncover novel TSSs. Our dataset can be thus used with high confidence to support gene annotation in dog and rat species. We identified 28,497 and 23,147 CAGE peaks, or promoter regions, for rat and dog respectively, and associated them to known genes. This approach could be seen as a standard method for improvement of existing gene models, as well as discovery of novel genes. Given that the FANTOM5 data collection includes dog and rat matched cell types in human and mouse as well, this data would also be useful for cross-species studies.
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- 2017
15. Transcribed enhancers lead waves of coordinated transcription in transitioning mammalian cells
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Christine L. Mummery, Hiroshi Kawamoto, Mitsuru Morimoto, Hiroki Sato, Misako Yoneda, Kim M. Summers, Haruhiko Koseki, Carsten O. Daub, Imad Abugessaisa, Olga Hrydziuszko, Akira Hasegawa, Afsaneh Eslami, J Kenneth Baillie, Dan Goldowitz, Frank Brombacher, Piero Carninci, Thomas J. Ha, Tomokatsu Ikawa, Peter G. Zhang, Andru Tomoiu, Erik Arner, Robin Andersson, Soichi Kojima, Margaret Patrikakis, Andreas Lennartsson, Christine A. Wells, Valerio Orlando, Miki Kojima, Lesley M. Forrester, Peter Arner, Marina Lizio, Christopher J. Mungall, Geoffrey J. Faulkner, Berit Lilje, David A. Hume, Takeya Kasukawa, Hideya Kawaji, Louise N. Winteringham, Soichi Ogishima, Kristoffer Vitting-Seerup, Jayson Harshbarger, Michael Detmar, Anita Schwegmann, Yasushi Okazaki, Rolf Swoboda, Alka Saxena, Jun Kawai, Hiromi Nishiyori-Sueki, Mitsuko Hara, Yoshihide Hayashizaki, Ernst J. Wolvetang, Chieko Kai, Naoto Kondo, Richard A Axton, Albin Sandelin, James Briggs, Yutaka Nakachi, Dmitry A. Ovchinnikov, Carmelo Ferrai, Mitsuyoshi Murata, Masayoshi Itoh, Finn Drabløs, Anthony G Beckhouse, Lynsey Fairbairn, Meenhard Herlyn, Mariko Okada-Hatakeyama, Beatrice Bodega, Susan E. Zabierowski, Morana Vitezic, Michiel J. L. de Hoon, Masaaki Furuno, Ana Pombo, Reto Guler, Hiroshi Tanaka, Alistair R. R. Forrest, Serkan Sahin, Timo Lassmann, Robert Passier, S. Peter Klinken, Tom C. Freeman, Alexander D. Diehl, Niklas Mejhert, Anna Ehrlund, Ken Miyaguchi, Michela Fagiolini, Nicolas Bertin, Michelle Rönnerblad, Sayaka Nagao-Sato, Levon M. Khachigian, Mitsuhiro Endoh, Margaret B. Davis, Shiro Fukuda, Daisuke Sugiyama, Xian-Yang Qin, Malcolm E. Fisher, Yosuke Mizuno, Jessica Severin, Sarah Klein, Suzana Savvi, Kelly J. Morris, Terrence F. Meehan, Yuri Ishizu, Fumi Hori, Ahmad M. N. Alhendi, Sachi Ishikawa-Kato, Tsugumi Kawashima, Harukazu Suzuki, Sugata Roy, and Chiyo Yanagi-Mizuochi
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Transcription, Genetic ,Cellular differentiation ,Enhancer RNAs ,Biology ,Article ,Mice ,Dogs ,Transcription (biology) ,Animals ,RNA, Messenger ,Enhancer ,Gene ,Transcription factor ,Genetics ,Regulation of gene expression ,Multidisciplinary ,Binding Sites ,Stem Cells ,Gene Expression Regulation, Developmental ,Promoter ,Cell Differentiation ,Cell biology ,Rats ,Enhancer Elements, Genetic ,Cattle ,Transcription Factors - Abstract
Uncaging promoter and enhancer dynamics In order to understand cellular differentiation, it is important to understand the timing of the regulation of gene expression. Arner et al. used cap analysis of gene expression (CAGE) to analyze gene enhancer and promoter activities in a number of human and mouse cell types. The RNA of enhancers was transcribed first, followed by that of transcription factors, and finally by genes that are not transcription factors. Science , this issue p. 1010
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- 2015
16. FANTOM5 CAGE profiles of human and mouse samples
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Jun Kawai, Anthony G Beckhouse, Dipti Vijayan, Michael Rehli, Toshiyuki Nakamura, Yuki Hasegawa, Timothy C. Barnett, Hisashi Shimoji, Erik Arner, Masayoshi Itoh, Masahide Hamaguchi, Sarah Klein, Reto Guler, Patrizia Rizzu, Atsutaka Kubosaki, Soichi Kojima, Timo Lassmann, Kelly J. Morris, Mutsumi Kanamori-Katayama, Ri Ichiroh Manabe, Hiromasa Morikawa, Kelly J Hitchens, Fumi Hori, Linda M. van den Berg, Yasushi Okazaki, Andru Tomoiu, Antti Sajantila, Akiko Saka, Thierry Sengstag, Alessandro Bonetti, Haruhiko Koseki, Matthias Edinger, Mitsuhiro Ohshima, Carsten O. Daub, Jayson Harshbarger, Sachi Ishikawa-Kato, Tsugumi Kawashima, Christine L. Mummery, Niklas Mejhert, Jun Takai, Dan Goldowitz, Naoko Suzuki, Guojun Sheng, David A. Hume, Hiroshi Kawamoto, Ai Kaiho, Jun Ichi Furusawa, Ailsa J Carlisle, Tomokatsu Ikawa, Shiro Fukuda, Peter G. Zhang, Akira Hasegawa, James Briggs, Toshio Kitamura, Alistair R. R. Forrest, Takahiro Arakawa, Marcvande Wetering, Shohei Noma, Fumio Nakahara, Jessica Severin, Sven Guhl, Atsushi Kondo, Mary C. Farach-Carson, Hans Clevers, Afsaneh Eslami, Christian Schmidl, Peter Heutink, Hideki Tatsukawa, Anita Schwegmann, Noriko Ninomiya, Antje Blumenthal, Yoshihide Hayashizaki, Suzana Savvi, Thomas J. Ha, Claudio Schneider, Daisuke Sugiyama, Hironori Satoh, Mitsuru Morimoto, Hiroki Sato, Yosuke Mizuno, Meenhard Herlyn, Hozumi Motohashi, Shigehiro Yoshida, Hiroo Toyoda, Christophe Simon, Piero Carninci, Tadasuke Nozaki, Hideya Kawaji, Louise N. Winteringham, Swati Pradhan-Bhatt, Imad Abugessaisa, Michihira Tagami, Tony J. Kenna, Yoko Yamaguchi, Geoffrey J. Faulkner, Alka Saxena, Naoto Kondo, Dmitry A. Ovchinnikov, Rie Fujita, Ernst J. Wolvetang, Michael Detmar, Miki Kojima, Peter Arner, Mitsuko Hara, Stefano Gustincich, Carrie A. Davis, Judith S. Kempfle, Margaret Patrikakis, Alan Mackay-Sim, Carmelo Ferrai, Yutaka Nakachi, Juha Kere, Mitsuyoshi Murata, Shimon Sakaguchi, Soichi Ogishima, Silvia Zucchelli, Andreas Lennartsson, Thomas R. Gingeras, Masanori Suzuki, Beatrice Bodega, Sugata Roy, Sayaka Nagao-Sato, Mitsuhiro Endoh, Anna Ehrlund, J Kenneth Baillie, Mizuho Sakai, Michela Fagiolini, Taeko Dohi, Christine A. Wells, Frank Brombacher, Masayuki Yamamoto, Robert Passier, Lynsey Fairbairn, Teunis B. H. Geijtenbeek, Shigeo Koyasu, Hiromi Nishiyori-Sueki, Yuri Ishizu, Yuki I. Kawamura, Chiyo Yanagi-Mizuochi, Roberto Verardo, Misako Yoneda, Mariko Okada-Hatakeyama, Kaoru Kaida, Ana Pombo, Gundula Schulze-Tanzil, Lesley M. Forrester, Kim M. Summers, Harukazu Suzuki, Naganari Ohkura, Weon Ju Lee, Hiroshi Tanaka, Alan J. Knox, Karl Ekwall, Yukio Nakamura, Serkan Sahin, Shuhei Noguchi, Hiroshi Ohno, Yohei Yonekura, Richard A Axton, Marina Lizio, S. Peter Klinken, Malcolm E. Fisher, Shoko Watanabe, Magda Babina, Xian-Yang Qin, Takaaki Sugiyama, B. Albert S. Edge, Eri Saijyo, Valerio Orlando, Takeya Kasukawa, Kazuyo Moro, Kenichi Nakazato, Naoko Takahashi, Levon M. Khachigian, Chieko Kai, Masaaki Furuno, Jay W. Shin, Hideki Enomoto, Hubrecht Institute for Developmental Biology and Stem Cell Research, AII - Infectious diseases, Infectious diseases, and AII - Amsterdam institute for Infection and Immunity
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0301 basic medicine ,500 Naturwissenschaften und Mathematik::570 Biowissenschaften ,Biologie ,Data Descriptor ,Molecular biology ,600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit ,Genome ,Mice ,0302 clinical medicine ,Transcription (biology) ,Promoter Regions, Genetic ,Non-U.S. Gov't ,Regulation of gene expression ,Research Support, Non-U.S. Gov't ,Statistics ,Computer Science Applications1707 Computer Vision and Pattern Recognition ,Computer Science Applications ,Library and Information Sciences ,Information Systems ,Statistics, Probability and Uncertainty ,Statistics and Probability ,ddc:500 ,Cell activation ,Systems biology ,Cell biology ,Computational biology ,Biology ,Research Support ,Education ,03 medical and health sciences ,Species Specificity ,Developmental biology ,Journal Article ,Animals ,Humans ,Enhancer ,Gene Expression Profiling ,Promoter ,Cap analysis gene expression ,Computational biology and bioinformatics ,Gene expression profiling ,030104 developmental biology ,Gene Expression Regulation ,Cardiovascular and Metabolic Diseases ,Probability and Uncertainty ,030217 neurology & neurosurgery - Abstract
Scientific Data, 4, ISSN:2052-4463
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- 2017
- Full Text
- View/download PDF
17. FANTOM5 CAGE profiles of human and mouse reprocessed for GRCh38 and GRCm38 genome assemblies
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Marina Lizio, Jayson Harshbarger, Jessica Severin, Piero Carninci, Akira Hasegawa, Imad Abugessaisa, Shuhei Noguchi, Takeya Kasukawa, Hideya Kawaji, and Atsushi Kondo
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0301 basic medicine ,Statistics and Probability ,Data Descriptor ,Computational biology ,Biology ,Library and Information Sciences ,Genome ,Education ,03 medical and health sciences ,Mice ,0302 clinical medicine ,Animals ,Humans ,Genome Reference Consortium ,Promoter Regions, Genetic ,Genetics ,Transcription initiation site ,Promoter ,Cap analysis gene expression ,Computer Science Applications ,Data processing ,030104 developmental biology ,Gene expression ,Statistics, Probability and Uncertainty ,Transcription Initiation Site ,030217 neurology & neurosurgery ,Information Systems - Abstract
The FANTOM5 consortium described the promoter-level expression atlas of human and mouse by using CAGE (Cap Analysis of Gene Expression) with single molecule sequencing. In the original publications, GRCh37/hg19 and NCBI37/mm9 assemblies were used as the reference genomes of human and mouse respectively; later, the Genome Reference Consortium released newer genome assemblies GRCh38/hg38 and GRCm38/mm10. To increase the utility of the atlas in forthcoming researches, we reprocessed the data to make them available on the recent genome assemblies. The data include observed frequencies of transcription starting sites (TSSs) based on the realignment of CAGE reads, and TSS peaks that are converted from those based on the previous reference. Annotations of the peak names were also updated based on the latest public databases. The reprocessed results enable us to examine frequencies of transcription initiations on the recent genome assemblies and to refer promoters with updated information across the genome assemblies consistently.
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- 2017
18. Transcription start site profiling of 15 anatomical regions of the Macaca mulatta central nervous system
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Shoko Watanabe, Ronald E. Bontrop, Luba M. Pardo, Margherita Francescatto, Mizuho Sakai, Alistair R. R. Forrest, Marina Lizio, Akira Hasegawa, Masayoshi Itoh, Patrizia Rizzu, Jessica Severin, Timo Lassmann, Hideya Kawaji, Piero Carninci, Takeya Kasukawa, Ingrid H.C.H.M. Philippens, Yoshihide Hayashizaki, Jayson Harshbarger, Imad Abugessaisa, and Peter Heutink
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Central Nervous System ,0301 basic medicine ,Statistics and Probability ,ved/biology.organism_classification_rank.species ,Computational biology ,Library and Information Sciences ,Macaque ,Genome ,Education ,Transcriptome ,03 medical and health sciences ,biology.animal ,anatomy & histology [Central Nervous System] ,Animals ,Author Correction ,Model organism ,Gene ,biology ,ved/biology ,Promoter ,biology.organism_classification ,Macaca mulatta ,Cap analysis gene expression ,Computer Science Applications ,Rhesus macaque ,030104 developmental biology ,Immunology ,ddc:500 ,Statistics, Probability and Uncertainty ,Transcription Initiation Site ,Information Systems - Abstract
Rhesus macaque was the second non-human primate whose genome has been fully sequenced and is one of the most used model organisms to study human biology and disease, thanks to the close evolutionary relationship between the two species. But compared to human, where several previously unknown RNAs have been uncovered, the macaque transcriptome is less studied. Publicly available RNA expression resources for macaque are limited, even for brain, which is highly relevant to study human cognitive abilities. In an effort to complement those resources, FANTOM5 profiled 15 distinct anatomical regions of the aged macaque central nervous system using Cap Analysis of Gene Expression, a high-resolution, annotation-independent technology that allows monitoring of transcription initiation events with high accuracy. We identified 25,869 CAGE peaks, representing bona fide promoters. For each peak we provide detailed annotation, expanding the landscape of ‘known’ macaque genes, and we show concrete examples on how to use the resulting data. We believe this data represents a useful resource to understand the central nervous system in macaque. Machine-accessible metadata file describing the reported data (ISA-Tab format)
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- 2017
19. An atlas of human long non-coding RNAs with accurate 5′ ends
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Yukio Nakamura, Mickal Mendez, Julian Gough, Jessica Severin, Owen J. L. Rackham, Dave Tang, A. Maxwell Burroughs, Masayoshi Itoh, Timo Lassmann, Carsten O. Daub, Leonard Lipovich, Erik Arner, Yoshihide Hayashizaki, Sarah Djebali, Soichi Kojima, Magda Babina, Shohei Noma, Piero Carninci, Hideya Kawaji, Sebastian Schmeier, Peter Heutink, Yulia A. Medvedeva, Tanvir Alam, Alison C. Testa, Elena Denisenko, Marina Lizio, Christine A. Wells, Chi Wai Yip, Akira Hasegawa, Jordan A. Ramilowski, Alistair R. R. Forrest, Michiel J. L. de Hoon, Harukazu Suzuki, Takeya Kasukawa, Nicolas Bertin, Thomas M. Poulsen, Imad Abugessaisa, Jayson Harshbarger, Chung-Chau Hon, Ctr Life Sci Technol, Div Gen Technol, Tsurumi Ku, RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN), Omics Sci Ctr, Tsurumi Ku, Ctr Translat Med, Canc Sci Inst Singapore, National University of Singapore (NUS), Human Longev Singapore Pte Ltd, Dept Comp Sci, Life Sci, University of Bristol [Bristol], Cardiovasc & Metab Disorders, Duke-NUS Medical School [Singapore], Inst Nat & Math Sci, Biotechnol Res Inst Drug Discovery BRD, Natl Inst Adv Ind Sci & Technol, Prevent Med & Diag Innovat Program, Natl Lib Med, Natl Ctr Biotechnol Informat, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Ctr Gen Regulat CRG, Barcelona Institute of Science and Technology (BIST), Universitat Pompeu Fabra [Barcelona] (UPF), Computat Biosci Res Ctr, Comp Elect & Math Sci & Engn Div, King Abdullah University of Science and Technology (KAUST), Biotechnol Res Ctr, Inst Bioengn, the Russian Academy of Sciences [Moscow, Russia] (RAS), Vavilov Inst Gen Genet, Russian Academy of Sciences [Moscow] (RAS), QEII Med Ctr, Harry Perkins Inst Med Res, The University of Western Australia (UWA), Med Res Ctr, Ctr Mol Med & Genet, Wayne State University [Detroit], Sch Med, Dept Neurol, Dept Comp Sci, North Dakota State University (NDSU), Telethon Kids Inst, German Research Center for Neurodegenerative Diseases - Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Dept Dermatol & Allergy, Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], Australian Inst Bioengn & Nanotechno, University of Queensland [Brisbane], Fac Med, Dept Anat & Neurosci, University of Melbourne, CLST Div Biofunct Dynam Imaging, BioResource Ctr, Cell Engn Div, Université de Tsukuba = University of Tsukuba, Dept Biosci & Nutr, Karolinska Institute, QEII Med Ctr, Harry Perkins Inst Med Re, Duke NUS Medical School, Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT], Universitat Pompeu Fabra [Barcelona], Russian Academy of Sciences, Wayne State University, Charité - Universitätsmedizin Berlin / Charite - University Medicine Berlin, and University of Tsukuba
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0301 basic medicine ,RNA Stability ,[SDV]Life Sciences [q-bio] ,genetics [Transcriptome] ,Datasets as Topic ,genetics [RNA, Long Noncoding] ,Genome ,Epigenesis, Genetic ,0302 clinical medicine ,Databases, Genetic ,Promoter Regions, Genetic ,Cells, Cultured ,Conserved Sequence ,Genetics ,Regulation of gene expression ,Multidisciplinary ,genetics [Organ Specificity] ,Genomics ,Enhancer Elements, Genetic ,annotation ,Organ Specificity ,030220 oncology & carcinogenesis ,RNA, Long Noncoding ,ddc:500 ,pr interval ,transcription ,architecture ,Quantitative Trait Loci ,Biology ,Polymorphism, Single Nucleotide ,Article ,genetics [RNA, Messenger] ,03 medical and health sciences ,seq ,evolution ,genetics [Conserved Sequence] ,Humans ,genetics [Genome, Human] ,RNA, Messenger ,Gene ,Internet ,genetics [Quantitative Trait Loci] ,Genome, Human ,Gene Expression Profiling ,genetics [Enhancer Elements, Genetic] ,Molecular Sequence Annotation ,landscape ,gene-expression ,Cap analysis gene expression ,promoter usage ,Gene expression profiling ,chemistry [RNA, Long Noncoding] ,030104 developmental biology ,Gene Expression Regulation ,genetics [Promoter Regions, Genetic] ,Expression quantitative trait loci ,genome-wide association ,Human genome ,Transcriptome ,Genome-Wide Association Study - Abstract
Long non-coding RNAs (lncRNAs) are largely heterogeneous and functionally uncharacterized. Here, using FANTOM5 cap analysis of gene expression (CAGE) data, we integrate multiple transcript collections to generate a comprehensive atlas of 27,919 human lncRNA genes with high-confidence 5' ends and expression profiles across 1,829 samples from the major human primary cell types and tissues. Genomic and epigenomic classification of these lncRNAs reveals that most intergenic lncRNAs originate from enhancers rather than from promoters. Incorporating genetic and expression data, we show that lncRNAs overlapping trait-associated single nucleotide polymorphisms are specifically expressed in cell types relevant to the traits, implicating these lncRNAs in multiple diseases. We further demonstrate that lncRNAs overlapping expression quantitative trait loci (eQTL)-associated single nucleotide polymorphisms of messenger RNAs are co-expressed with the corresponding messenger RNAs, suggesting their potential roles in transcriptional regulation. Combining these findings with conservation data, we identify 19,175 potentially functional lncRNAs in the human genome.
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- 2017
20. DEIVA: a web application for interactive visual analysis of differential gene expression profiles
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Piero Carninci, Anton Kratz, and Jayson Harshbarger
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0301 basic medicine ,Statistics as Topic ,Biology ,computer.software_genre ,03 medical and health sciences ,User-Computer Interface ,0302 clinical medicine ,Software ,Interactive visual analysis ,Genetics ,Computer Graphics ,Web application ,Differential gene expression ,Statistical hypothesis testing ,Visualization ,User Friendly ,Internet ,business.industry ,Gene Expression Profiling ,fungi ,Usability ,Single-page application ,030104 developmental biology ,030220 oncology & carcinogenesis ,Data mining ,RNA-seq ,business ,computer ,Biotechnology - Abstract
Background Differential gene expression (DGE) analysis is a technique to identify statistically significant differences in RNA abundance for genes or arbitrary features between different biological states. The result of a DGE test is typically further analyzed using statistical software, spreadsheets or custom ad hoc algorithms. We identified a need for a web-based system to share DGE statistical test results, and locate and identify genes in DGE statistical test results with a very low barrier of entry. Results We have developed DEIVA, a free and open source, browser-based single page application (SPA) with a strong emphasis on being user friendly that enables locating and identifying single or multiple genes in an immediate, interactive, and intuitive manner. By design, DEIVA scales with very large numbers of users and datasets. Conclusions Compared to existing software, DEIVA offers a unique combination of design decisions that enable inspection and analysis of DGE statistical test results with an emphasis on ease of use.
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- 2016
21. Correction: Corrigendum: A draft network of ligand-receptor-mediated multicellular signalling in human
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Masayoshi Itoh, Venkata P. Satagopam, Jayson Harshbarger, Burkhard Rost, Piero Carninci, Hideya Kawaji, Tatyana Goldberg, Edda Kloppmann, Jordan A. Ramilowski, Alistair R. R. Forrest, and Marina Lizio
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0301 basic medicine ,Multidisciplinary ,Science ,Published Erratum ,General Physics and Astronomy ,General Chemistry ,Receptor-mediated endocytosis ,Computational biology ,Biology ,Ligand (biochemistry) ,Bioinformatics ,General Biochemistry, Genetics and Molecular Biology ,Spelling ,03 medical and health sciences ,Multicellular organism ,030104 developmental biology ,Signalling - Abstract
Nature Communications 6: Article number: 786610.1038/ncomms8866 (2015); Published: July222015; Updated: February102016. The original version of this Article contained an error in the spelling of the author Edda Kloppmann, which was incorrectly given as Edda Kloppman. This has now been corrected in both the PDF and HTML versions of the Article.
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- 2016
22. A draft network of ligand–receptor-mediated multicellular signalling in human
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Tatyana Goldberg, Edda Kloppmann, Hideya Kawaji, Venkata P. Satagopam, Burkhard Rost, Jordan A. Ramilowski, Alistair R. R. Forrest, Jayson Harshbarger, Piero Carninci, Masayoshi Itoh, Marina Lizio, and Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) [research center]
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0303 health sciences ,Cell signaling ,Cell type ,Multidisciplinary ,General Physics and Astronomy ,Multidisciplinary, general & others [F99] [Life sciences] ,General Chemistry ,Receptor-mediated endocytosis ,Biology ,Bioinformatics ,Article ,General Biochemistry, Genetics and Molecular Biology ,ddc ,Cell biology ,Multidisciplinaire, généralités & autres [F99] [Sciences du vivant] ,03 medical and health sciences ,Multicellular organism ,0302 clinical medicine ,Secretory protein ,Signalling ,030220 oncology & carcinogenesis ,Receptor ,Autocrine signalling ,030304 developmental biology - Abstract
Cell-to-cell communication across multiple cell types and tissues strictly governs proper functioning of metazoans and extensively relies on interactions between secreted ligands and cell-surface receptors. Herein, we present the first large-scale map of cell-to-cell communication between 144 human primary cell types. We reveal that most cells express tens to hundreds of ligands and receptors to create a highly connected signalling network through multiple ligand–receptor paths. We also observe extensive autocrine signalling with approximately two-thirds of partners possibly interacting on the same cell type. We find that plasma membrane and secreted proteins have the highest cell-type specificity, they are evolutionarily younger than intracellular proteins, and that most receptors had evolved before their ligands. We provide an online tool to interactively query and visualize our networks and demonstrate how this tool can reveal novel cell-to-cell interactions with the prediction that mast cells signal to monoblastic lineages via the CSF1–CSF1R interacting pair., Cell-to-cell communication relies upon interactions between secreted ligands and cell surface receptors. Here, Ramilowski et al. present a draft cell-to-cell communication network based on expression of ligand-receptor pairs in 144 different human cell types.
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- 2015
23. Gateways to the FANTOM5 promoter level mammalian expression atlas
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Masayoshi Itoh, Jayson Harshbarger, Fumi Hori, Toshiaki Katayama, Sachi Ishikawa-Kato, Derek W. Wright, Erik Arner, Yoshihide Hayashizaki, Hisashi Shimoji, Shiro Fukuda, Hiromasa Ono, Terrence F. Meehan, Rajaram Kaliyaperumal, Jessica Severin, Michael Rehli, Takeya Kasukawa, J Kenneth Baillie, Albin Sandelin, Carsten O. Daub, Alistair R. R. Forrest, Timo Lassmann, Hideya Kawaji, Tetsuro Toyoda, Tom C. Freeman, Alexander D. Diehl, Serkan Sahin, Erik Anthony Schultes, Piero Carninci, Hidemasa Bono, Emmanuel Dimont, Nicolas Bertin, Winston Hide, Kaori Fujieda, Koro Nishikata, Imad Abugessaisa, Christopher J. Mungall, Mark Thompson, Peter A C 't Hoen, Marina Lizio, Michiel J. L. de Hoon, and Zuotian Tatum
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ANALYSIS GENE-EXPRESSION ,DATABASE ,Datasets as Topic ,Genomics ,Computational biology ,Biology ,Ontology (information science) ,MOUSE ,TRANSCRIPTIONAL LANDSCAPE ,03 medical and health sciences ,Mice ,User-Computer Interface ,0302 clinical medicine ,CAP-ANALYSIS ,Databases, Genetic ,HUMAN GENOME ,Animals ,Humans ,RNA-SEQ ,Enhancer ,Promoter Regions, Genetic ,Transcription factor ,Gene ,Transcription Initiation, Genetic ,030304 developmental biology ,computer.programming_language ,Genetics ,NATIONAL CENTER ,0303 health sciences ,Gene Expression Profiling ,Fantom ,Computational Biology ,ONTOLOGIES ,Gene expression profiling ,Human genome ,Transcriptome ,computer ,FUNCTIONAL ANNOTATION ,030217 neurology & neurosurgery ,Software - Abstract
The FANTOM5 project investigates transcription initiation activities in more than 1,000 human and mouse primary cells, cell lines and tissues using CAGE. Based on manual curation of sample information and development of an ontology for sample classification, we assemble the resulting data into a centralized data resource (http://fantom.gsc.riken.jp/5/). This resource contains web-based tools and data-access points for the research community to search and extract data related to samples, genes, promoter activities, transcription factors and enhancers across the FANTOM5 atlas. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0560-6) contains supplementary material, which is available to authorized users.
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- 2015
24. The BioMart community portal: an innovative alternative to large, centralized data repositories
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Byung Woo Han, Jose Manuel Garcia-Manteiga, Alejandro Maass, Jayson Harshbarger, Daniel M. Staines, Zhengyan Kan, Davide Rambaldi, Dong Jin Han, Richard Baldock, Ji Hyun Lee, Merideth Bonierbale, Hadi Quesneville, Anthony Esposito, Thomas Letellier, Jun Wang, Steven Rosanoff, Céline Noirot, Richard D. Hayes, Sarah W. Burge, Anthony J. Brookes, Gabriele Bucci, Giulia Barbiera, Elia Stupka, Olivier Arnaiz, Thomas Maurel, Shen Hu, Olivier Sallou, Emanuela Gadaleta, Jérôme Mariette, Rosalind J. Cutts, Joseph W. Carlson, Damian Smedley, Robert C. Free, James E. Allen, Simon A. Forbes, Kevin R. Stone, Jie Luo, Andrew Blake, Chu Jun Liu, Takatomo Fujisawa, Jon W. Teague, Cristian Perez-Llamas, Rebecca Shepherd, Julio Fernandez-Banet, Raul Cordova, David Goodstein, Shi Jian Zhang, Ken Youens-Clark, Cédric Cabau, José Afonso Guerra-Assunção, Iwan Buetti, Stefania Merella, Delphine Steinbach, Linda Sperling, Robert K. Hastings, Abu Z. Dayem Ullah, Claude Chelala, Erik Dassi, Eduardo Eyras, Sunghoon Kim, Kristian Gray, Dejan Lazarevic, Luca Pandini, Azza M. Mohamed, Doreen Ware, William Spooner, Alex Di Genova, Daniel Lawson, Alessandro Quattrone, Davide Cittaro, Heather Estrella, Rhoda Kinsella, Chuan-Yun Li, Christophe Klopp, Aminah Keliet, Michela Riba, Zhi-Liang Hu, Hideya Kawaji, Arnaud Kerhornou, James M. Reecy, Tim Beck, Charalambos Chrysostomou, François Moreews, Nelson Ndegwa, Arek Kasprzyk, Michael Primig, Claire Hoede, Ibounyamine Nabihoudine, Amonida Zadissa, Paolo Provero, Reinhard Simon, Todd W. Harris, Bernard Haggarty, Lucie N. Hutchins, Marie Wong-Erasmus, Philippe Bardou, Elisa Salas, Lei Kong, Anis Djari, Syed Haider, Steffen Durinck, Mohammad Awedh, Pietro Liò, Amna A. Saddiq, Olivier Collin, European Bioinformatics Institute [Hinxton] (EMBL-EBI), EMBL Heidelberg, Computer Laboratory [Cambridge], University of Cambridge [UK] (CAM), Genentech, Inc., Genentech, Inc. [San Francisco], San Raffaele Scientific Institute, Vita-Salute San Raffaele University and Center for Translational Genomics and Bioinformatics, Genetics, Biology and Biochemistry, Molecular Biotechnology Centre, Centre de génétique moléculaire (CGM), Université Paris-Sud - Paris 11 (UP11)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), King Abdulaziz University, MRC Human Genetics Unit, University of Edinburgh-Western General Hospital, Laboratoire de Génétique Cellulaire (LGC), Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA), Department of Genetics [Leicester], University of Leicester, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Medical Research Counc, International Potato Center, Department of Energy / Joint Genome Institute (DOE), Los Alamos National Laboratory (LANL), Centre for Molecular Oncology and Imaging, Centre for Molecular Oncology and Imaging, Barts Cancer Institute, Plateforme bioinformatique GenOuest [Rennes], Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Plateforme Génomique Santé Biogenouest®-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Rennes (ENS Rennes)-Télécom Bretagne-CentraleSupélec, University of Trento [Trento], University of Chile [Santiago], Unité de Biométrie et Intelligence Artificielle (UBIA), Institut National de la Recherche Agronomique (INRA), Pfizer Oncology, Institució Catalana de Recerca i Estudis Avançats (ICREA), Cancer Genome Project, The Wellcome Trust Sanger Institute [Cambridge], Kasuza DNA Research Institute, Seoul National University [Seoul] (SNU), Cold Spring Harbor Laboratory (CSHL), RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN), School of Dentistry and Dental Research Institute [UCLA], University of California [Los Angeles] (UCLA), University of California-University of California, Department of Animal Science and Center for Integrated Animal Genomics, Iowa State University (ISU), Mouse Genomic Informatics Group (MGI), The Jackson Laboratory, Unité de Recherche Génomique Info (URGI), Center for Bioinformatics [Pekin], Peking University [Beijing], Division of Industrial Ecology (KTH), Royal Institute of Technology [Stockholm] (KTH ), Institute of Molecular Medicine, Universidad de Santiago de Chile [Santiago] (USACH), Centro de Regulación Génica (CRG), Pontificia Universidad Católica de Chile (UC)-Universidad Andrés Bello [Santiago] (UNAB)-Universidad de Santiago de Chile [Santiago] (USACH), Centre de Modélisation Mathématique / Centro de Modelamiento Matemático (CMM), Centre National de la Recherche Scientifique (CNRS), Unité Mathématiques et Informatique Appliquées de Toulouse (MIAT), Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), Unité de Mathématiques et Informatique Appliquées de Toulouse (MIAT INRA), Mathématiques et Informatique Appliquées Toulouse, Universitat Pompeu Fabra [Barcelona], Institut de recherche en santé, environnement et travail (Irset), Université d'Angers (UA)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Department of Animal Science, Eagle Genomics Ltd, Eagle Genomics, State Key Laboratory of Lithospheric Evolution (SKL), Institute of Geology and Geophysics [Beijing] (IGG), Chinese Academy of Sciences [Beijing] (CAS)-Chinese Academy of Sciences [Beijing] (CAS), University of the Chinese Academy of Sciences, Ontario Institute for Cancer Research [Canada] (OICR), Ontario Institute for Cancer Research, Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, International Potato Center [Lima] (CIP), Consultative Group on International Agricultural Research [CGIAR] (CGIAR), GESTION DES DONNÉES ET DE LA CONNAISSANCE (IRISA-D7), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Plateforme Génomique Santé Biogenouest®-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria), Universidad de Chile = University of Chile [Santiago] (UCHILE), The Jackson Laboratory [Bar Harbor] (JAX), Center for Bioinformatics [Peking], Pontificia Universidad Católica de Chile (UC)-Universidad Andrés Bello [Santiago] (UNAB), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, 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), Universitat Pompeu Fabra [Barcelona] (UPF), Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )-Institut National de la Santé et de la Recherche Médicale (INSERM)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Université d'Angers (UA), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT), Université de Rennes (UR)-Plateforme Génomique Santé Biogenouest®-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-GESTION DES DONNÉES ET DE LA CONNAISSANCE (IRISA-D7), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Unité de Biométrie et Intelligence Artificielle (ancêtre de MIAT) (UBIA), University of California (UC)-University of California (UC), Université d'Angers (UA)-Université de Rennes (UR)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Jonchère, Laurent, CentraleSupélec-Télécom Bretagne-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Télécom Bretagne-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Plateforme Génomique Santé Biogenouest®-Inria Rennes – Bretagne Atlantique, Lio, Pietro [0000-0002-0540-5053], and Apollo - University of Cambridge Repository
- Subjects
Proteomics ,Interface (Java) ,Data management ,[SDV]Life Sciences [q-bio] ,génomique fonctionnelle ,Biology ,Ontology (information science) ,computer.software_genre ,World Wide Web ,Genomics ,Humans ,Internet ,Neoplasms ,Database Management Systems ,Genetics ,cancer ,Web Server issue ,protéomique ,ontologie ,ComputingMilieux_MISCELLANEOUS ,base de données ,business.industry ,Toolbox ,[SDV] Life Sciences [q-bio] ,espèce modèle ,Scalability ,The Internet ,Web service ,business ,Host (network) ,computer - Abstract
International audience; The BioMart Community Portal (www.biomart.org) is a community-driven effort to provide a unified interface to biomedical databases that are distributed worldwide. The portal provides access to numerous database projects supported by 30 scientific organizations. It includes over 800 different biological datasets spanning genomics, proteomics, model organisms, cancer data, ontology information and more. All resources available through the portal are independently administered and funded by their host organizations. The BioMart data federation technology provides a unified interface to all the available data. The latest version of the portal comes with many new databases that have been created by our ever-growing community. It also comes with better support and extensibility for data analysis and visualization tools. A new addition to our toolbox, the enrichment analysis tool is now accessible through graphical and web service interface. The BioMart community portal averages over one million requests per day. Building on this level of service and the wealth of information that has become available, the BioMart Community Portal has introduced a new, more scalable and cheaper alternative to the large data stores maintained by specialized organizations.
- Published
- 2015
25. Interactive visualization and analysis of large-scale sequencing datasets using ZENBU
- Author
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Yoshihide Hayashizaki, Alistair R. R. Forrest, Carsten O. Daub, Jayson Harshbarger, Jessica Severin, Nicolas Bertin, Hideya Kawaji, and Marina Lizio
- Subjects
Internet ,business.industry ,Computer science ,Sequence analysis ,Sequence Analysis, RNA ,Gene Expression Profiling ,Biomedical Engineering ,Bioengineering ,Genomics ,Computational biology ,Applied Microbiology and Biotechnology ,Cap analysis gene expression ,Gene expression profiling ,User-Computer Interface ,Software ,Molecular Medicine ,Humans ,The Internet ,business ,Large-Scale Sequencing ,Interactive visualization ,Biotechnology - Published
- 2014
26. FANTOM5 transcriptome catalog of cellular states based on Semantic MediaWiki
- Author
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Jayson Harshbarger, Hideya Kawaji, Imad Abugessaisa, Yoshihide Hayashizaki, Piero Carninci, Takeya Kasukawa, Serkan Sahin, Atsushi Kondo, Marina Lizio, Alistair R. R. Forrest, and Hisashi Shimoji
- Subjects
0301 basic medicine ,Computer science ,Computational biology ,Genome ,General Biochemistry, Genetics and Molecular Biology ,Transcriptome ,World Wide Web ,03 medical and health sciences ,Software ,Resource (project management) ,Animals ,Humans ,computer.programming_language ,Biological data ,Genome, Human ,business.industry ,Experimental data ,Fantom ,Semantics ,Data set ,030104 developmental biology ,Original Article ,Transcription Initiation Site ,Databases, Nucleic Acid ,General Agricultural and Biological Sciences ,business ,computer ,Information Systems - Abstract
The Functional Annotation of the Mammalian Genome project (FANTOM5) mapped transcription start sites (TSSs) and measured their activities in a diverse range of biological samples. The FANTOM5 project generated a large data set; including detailed information about the profiled samples, the uncovered TSSs at high base-pair resolution on the genome, their transcriptional initiation activities, and further information of transcriptional regulation. Data sets to explore transcriptome in individual cellular states encoded in the mammalian genomes have been enriched by a series of additional analysis, based on the raw experimental data, along with the progress of the research activities. To make the heterogeneous data set accessible and useful for investigators, we developed a web-based database called Semantic catalog of Samples, Transcription initiation And Regulators (SSTAR). SSTAR utilizes the open source wiki software MediaWiki along with the Semantic MediaWiki (SMW) extension, which provides flexibility to model, store, and display a series of data sets produced during the course of the FANTOM5 project. Our use of SMW demonstrates the utility of the framework for dissemination of large-scale analysis results. SSTAR is a case study in handling biological data generated from a large-scale research project in terms of maintenance and growth alongside research activities. Database URL: http://fantom.gsc.riken.jp/5/sstar/
- Published
- 2016
27. A promoter-level mammalian expression atlas
- Author
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Frank Brombacher, Wyeth W. Wasserman, Hiromasa Morikawa, Fumi Hori, Sayaka Nagao-Sato, Artem S. Kasianov, Mitsuhiro Endoh, Ilka Hoof, Hans Clevers, Hideki Tatsukawa, Anita Schwegmann, Kang Li, David A. de Lima Morais, Yoshihide Hayashizaki, Morana Vitezic, Judith A. Blake, Leonard Lipovich, Hozumi Motohashi, Timothy Ravasi, Meenhard Herlyn, Shuji Kawaguchi, Antti Sajantila, Haruhiko Koseki, Lukasz Huminiecki, Tsugumi Kawashima, Carrie A. Davis, Mamoon Rashid, Winston Hide, Alka Saxena, Mizuho Sakai, Carsten O. Daub, Kim M. Summers, Yuki Hasegawa, Hisashi Shimoji, Margaret Patrikakis, Efthymios Motakis, Morten Beck Rye, Dan Goldowitz, Masaaki Furuno, Lynsey Fairbairn, Alan Mackay-Sim, Andreas Lennartsson, John A.C. Archer, Mitsuru Morimoto, Harukazu Suzuki, Silvia Zucchelli, Weon Ju Lee, Hiroki Sato, Alan J. Knox, Margherita Francescatto, Xiaobei Zhao, Jay W. Shin, Thomas R. Gingeras, Soichi Ogishima, Jayson Harshbarger, Mark Thompson, Beatrice Bodega, Marco Chierici, Shintaro Katayama, Albin Sandelin, Sarah Rennie, Silvano Piazza, Tomokatsu Ikawa, Matthias Harbers, Magda Babina, Peter G. Zhang, Gabriel M. Altschule, Lenhard Vladimir B. Bajic, Andrew P. Gibson, Malcolm E. Fisher, Karl Ekwall, Yukio Nakamura, Arnab Pain, Michiel J. L. de Hoon, Toshio Kitamura, Anthony G Beckhouse, Ai Kaiho, Julian Gough, James Briggs, Jordan A. Ramilowski, Miki Kojima, Alistair R. R. Forrest, Erik Anthony Schultes, Jessica C. Mar, Dipti Vijayan, Peter Arner, S. Peter Klinken, Michael Rehli, Kazuhiro Kajiyama, Christophe Simon, Piero Carninci, Marco Roncador, Shigeo Koyasu, Mary C. Farach-Carson, Shigehiro Yoshida, Swati Pradhan-Bhatt, Zuotian Tatum, Masanori Suzuki, Mette C. Jørgensen, Benoit Marchand, Misako Yoneda, James Prendergast, Noriko Ninomiya, Tom C. Freeman, Yulia A. Medvedeva, Niklas Mejhert, Jun Takai, Alexander D. Diehl, Akiko Saka, Marc van de Wetering, Takehiro Hashimoto, Naoto Kondo, Martin S. Taylor, Albert S.B. Edge, Mutsumi Kanamori-Katayama, Colin A. Semple, Alexander V. Favorov, Giuseppe Jurman, Toshiyuki Nakamura, Thomas J. Ha, Yuri Ishizu, Shannan J. Ho Sui, David A. Hume, Owen J. L. Rackham, Michela Fagiolini, Daisuke Sugiyama, Helena Persson, Hironori Satoh, Robert Young, Emily J. Wood, Akira Hasegawa, Yosuke Mizuno, Juha Kere, Hiroshi Tanaka, Michihira Tagami, A. Maxwell Burroughs, Sugata Roy, Sachi Kato, Taeko Dohi, Hai Fang, Chieko Kai, Fumio Nakahara, Christian Schmidl, Hiromi Nishiyori, Thierry Sengstag, Sven Guhl, Kei Iida, Antje Blumenthal, Boris Lenhard, Sarah Krampitz, Peter A C 't Hoen, Piotr J. Balwierz, Masayuki Yamamoto, Eri Saijyo, Suzana Savvi, Intikhab Alam Altschuler, Marina Lizio, Alison M. Meynert, Kazuyo Moro, Kenichi Nakazato, Sebastian Schmeier, Carlo Vittorio Cannistraci, Yasushi Okazaki, Yishai Shimoni, Kelly J Hitchens, Hideki Enomoto, Jeroen F. J. Laros, Naganari Ohkura, Ilya E. Vorontsov, Davide Albanese, Hiroshi Ohno, Yun Chen, Terrence F. Meehan, Mitsuhiro Ohshima, Mitsuko Hara, Emiliano Dalla, Roberto Verardo, Claudio Schneider, Takahiro Arakawa, Oliver Hofmann, Matthias Edinger, Mariko Okada-Hatakeyama, Susan E. Zabierowski, Shohei Noma, Yutaka Nakachi, Shoko Watanabe, Kaoru Kaida, Mitsuyoshi Murata, Takaaki Sugiyama, Hui Jia, Tetsuro Toyoda, Naoko Suzuki, Vsevolod J. Makeev, Naoko Takahashi Tagami, Hiroko Ohmiya, Christine L. Mummery, Emmanuel Dimont, Shiro Fukuda, Jun Kawai, Ivan V. Kulakovskiy, Anthony Mathelier, Nicolas Bertin, Hiroshi Kawamoto, Vanja Haberle, Robert Passier, Levon M. Khachigian, Yuki I. Kawamura, Jessica Severin, Valerio Orlando, Takeya Kasukawa, Teunis B. H. Geijtenbeek, Charles Plessy, Ernst J. Wolvetang, Stefano Gustincich, Shimon Sakaguchi, Erik van Nimwegen, Reto Guler, Martin C. Frith, Andrea Califano, Timo Lassmann, Peter Heutink, Boris R. Jankovic, Ri Ichiroh Manabe, Berit Lilje, Yari Ciani, Erik Arner, Rie Fujita, Robin Andersson, J Kenneth Baillie, Andrew T. Kwon, Atsutaka Kubosaki, Jun Ichi Furusawa, Soichi Kojima, Daniel Carbajo, Christine A. Wells, Tadasuke Nozaki, Rolf Swoboda, Hiroo Toyoda, Tony J. Kenna, Yoko Yamaguchi, Hideya Kawaji, Louise N. Winteringham, Cesare Furlanello, Michael Detmar, Judith S. Kempfle, Bogumil Kaczkowski, Gundula G. Schulze-Tanzil, Linda M. van den Berg, Alessandro Bonetti, Eivind Valen, Masayoshi Itoh, Yohei Yonekura, Guojun Sheng, Ulf Schaefer, Masahide Hamaguchi, Patrizia Rizzu, Anagha Joshi, Dmitry A. Ovchinnikov, Finn Drabløs, Christopher J. Mungall, Geoffrey J. Faulkner, Hubrecht Institute for Developmental Biology and Stem Cell Research, AII - Amsterdam institute for Infection and Immunity, Infectious diseases, Experimental Immunology, Human genetics, and NCA - Brain mechanisms in health and disease
- Subjects
Transcription, Genetic ,Cells ,Messenger ,Gene regulatory network ,Mammalian promoter database ,Biology ,Article ,Cell Line ,Promoter Regions ,Mice ,Open Reading Frames ,Essential ,Atlases as Topic ,Genetic ,Animals ,Cluster Analysis ,Humans ,Gene Regulatory Networks ,RNA, Messenger ,Promoter Regions, Genetic ,Gene ,Transcription factor ,Cells, Cultured ,Conserved Sequence ,Genetics ,Regulation of gene expression ,Cultured ,Multidisciplinary ,Genes, Essential ,Genome ,Promoter ,Molecular Sequence Annotation ,Cap analysis gene expression ,Genes ,Gene Expression Regulation ,Organ Specificity ,Transcription Factors ,Transcription Initiation Site ,Transcriptome ,RNA ,Human genome ,Transcription - Abstract
Regulated transcription controls the diversity, developmental pathways and spatial organization of the hundreds of cell types that make up a mammal. Using single-molecule cDNA sequencing, we mapped transcription start sites (TSSs) and their usage in human and mouse primary cells, cell lines and tissues to produce a comprehensive overview of mammalian gene expression across the human body. We find that few genes are truly 'housekeeping', whereas many mammalian promoters are composite entities composed of several closely separated TSSs, with independent cell-type-specific expression profiles. TSSs specific to different cell types evolve at different rates, whereas promoters of broadly expressed genes are the most conserved. Promoter-based expression analysis reveals key transcription factors defining cell states and links them to binding-site motifs. The functions of identified novel transcripts can be predicted by coexpression and sample ontology enrichment analyses. The functional annotation of the mammalian genome 5 (FANTOM5) project provides comprehensive expression profiles and functional annotation of mammalian cell-type-specific transcriptomes with wide applications in biomedical research.
- Published
- 2014
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