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3 results on '"Kanamori-Katayama M"'

1. Comparison of CAGE and RNA-seq transcriptome profiling using clonally amplified and single-molecule next-generation sequencing.

Author

Kawaji H, Lizio M, Itoh M, Kanamori-Katayama M, Kaiho A, Nishiyori-Sueki H, Shin JW, Kojima-Ishiyama M, Kawano M, Murata M, Ninomiya-Fukuda N, Ishikawa-Kato S, Nagao-Sato S, Noma S, Hayashizaki Y, Forrest AR, and Carninci P

Subjects
Gene Expression Profiling, Humans, Sequence Analysis, RNA methods, High-Throughput Nucleotide Sequencing methods, RNA genetics, Transcriptome genetics
Abstract

CAGE (cap analysis gene expression) and RNA-seq are two major technologies used to identify transcript abundances as well as structures. They measure expression by sequencing from either the 5' end of capped molecules (CAGE) or tags randomly distributed along the length of a transcript (RNA-seq). Library protocols for clonally amplified (Illumina, SOLiD, 454 Life Sciences [Roche], Ion Torrent), second-generation sequencing platforms typically employ PCR preamplification prior to clonal amplification, while third-generation, single-molecule sequencers can sequence unamplified libraries. Although these transcriptome profiling platforms have been demonstrated to be individually reproducible, no systematic comparison has been carried out between them. Here we compare CAGE, using both second- and third-generation sequencers, and RNA-seq, using a second-generation sequencer based on a panel of RNA mixtures from two human cell lines to examine power in the discrimination of biological states, detection of differentially expressed genes, linearity of measurements, and quantification reproducibility. We found that the quantified levels of gene expression are largely comparable across platforms and conclude that CAGE and RNA-seq are complementary technologies that can be used to improve incomplete gene models. We also found systematic bias in the second- and third-generation platforms, which is likely due to steps such as linker ligation, cleavage by restriction enzymes, and PCR amplification. This study provides a perspective on the performance of these platforms, which will be a baseline in the design of further experiments to tackle complex transcriptomes uncovered in a wide range of cell types.

Published
2014
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2. A promoter-level mammalian expression atlas.

Author

Forrest AR, Kawaji H, Rehli M, Baillie JK, de Hoon MJ, Haberle V, Lassmann T, Kulakovskiy IV, Lizio M, Itoh M, Andersson R, Mungall CJ, Meehan TF, Schmeier S, Bertin N, Jørgensen M, Dimont E, Arner E, Schmidl C, Schaefer U, Medvedeva YA, Plessy C, Vitezic M, Severin J, Semple C, Ishizu Y, Young RS, Francescatto M, Alam I, Albanese D, Altschuler GM, Arakawa T, Archer JA, Arner P, Babina M, Rennie S, Balwierz PJ, Beckhouse AG, Pradhan-Bhatt S, Blake JA, Blumenthal A, Bodega B, Bonetti A, Briggs J, Brombacher F, Burroughs AM, Califano A, Cannistraci CV, Carbajo D, Chen Y, Chierici M, Ciani Y, Clevers HC, Dalla E, Davis CA, Detmar M, Diehl AD, Dohi T, Drabløs F, Edge AS, Edinger M, Ekwall K, Endoh M, Enomoto H, Fagiolini M, Fairbairn L, Fang H, Farach-Carson MC, Faulkner GJ, Favorov AV, Fisher ME, Frith MC, Fujita R, Fukuda S, Furlanello C, Furino M, Furusawa J, Geijtenbeek TB, Gibson AP, Gingeras T, Goldowitz D, Gough J, Guhl S, Guler R, Gustincich S, Ha TJ, Hamaguchi M, Hara M, Harbers M, Harshbarger J, Hasegawa A, Hasegawa Y, Hashimoto T, Herlyn M, Hitchens KJ, Ho Sui SJ, Hofmann OM, Hoof I, Hori F, Huminiecki L, Iida K, Ikawa T, Jankovic BR, Jia H, Joshi A, Jurman G, Kaczkowski B, Kai C, Kaida K, Kaiho A, Kajiyama K, Kanamori-Katayama M, Kasianov AS, Kasukawa T, Katayama S, Kato S, Kawaguchi S, Kawamoto H, Kawamura YI, Kawashima T, Kempfle JS, Kenna TJ, Kere J, Khachigian LM, Kitamura T, Klinken SP, Knox AJ, Kojima M, Kojima S, Kondo N, Koseki H, Koyasu S, Krampitz S, Kubosaki A, Kwon AT, Laros JF, Lee W, Lennartsson A, Li K, Lilje B, Lipovich L, Mackay-Sim A, Manabe R, Mar JC, Marchand B, Mathelier A, Mejhert N, Meynert A, Mizuno Y, de Lima Morais DA, Morikawa H, Morimoto M, Moro K, Motakis E, Motohashi H, Mummery CL, Murata M, Nagao-Sato S, Nakachi Y, Nakahara F, Nakamura T, Nakamura Y, Nakazato K, van Nimwegen E, Ninomiya N, Nishiyori H, Noma S, Noma S, Noazaki T, Ogishima S, Ohkura N, Ohimiya H, Ohno H, Ohshima M, Okada-Hatakeyama M, Okazaki Y, Orlando V, Ovchinnikov DA, Pain A, Passier R, Patrikakis M, Persson H, Piazza S, Prendergast JG, Rackham OJ, Ramilowski JA, Rashid M, Ravasi T, Rizzu P, Roncador M, Roy S, Rye MB, Saijyo E, Sajantila A, Saka A, Sakaguchi S, Sakai M, Sato H, Savvi S, Saxena A, Schneider C, Schultes EA, Schulze-Tanzil GG, Schwegmann A, Sengstag T, Sheng G, Shimoji H, Shimoni Y, Shin JW, Simon C, Sugiyama D, Sugiyama T, Suzuki M, Suzuki N, Swoboda RK, 't Hoen PA, Tagami M, Takahashi N, Takai J, Tanaka H, Tatsukawa H, Tatum Z, Thompson M, Toyodo H, Toyoda T, Valen E, van de Wetering M, van den Berg LM, Verado R, Vijayan D, Vorontsov IE, Wasserman WW, Watanabe S, Wells CA, Winteringham LN, Wolvetang E, Wood EJ, Yamaguchi Y, Yamamoto M, Yoneda M, Yonekura Y, Yoshida S, Zabierowski SE, Zhang PG, Zhao X, Zucchelli S, Summers KM, Suzuki H, Daub CO, Kawai J, Heutink P, Hide W, Freeman TC, Lenhard B, Bajic VB, Taylor MS, Makeev VJ, Sandelin A, Hume DA, Carninci P, and Hayashizaki Y

Subjects
Animals, Cell Line, Cells, Cultured, Cluster Analysis, Conserved Sequence genetics, Gene Expression Regulation genetics, Gene Regulatory Networks genetics, Genes, Essential genetics, Genome genetics, Humans, Mice, Open Reading Frames genetics, Organ Specificity, RNA, Messenger analysis, RNA, Messenger genetics, Transcription Factors metabolism, Transcription Initiation Site, Transcription, Genetic genetics, Atlases as Topic, Molecular Sequence Annotation, Promoter Regions, Genetic genetics, Transcriptome genetics
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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3. The statistical geometry of transcriptome divergence in cell-type evolution and cancer

Author

Liang, C, Alam, I, Albanese, D, Altschuler, G, Andersson, R, Arakawa, T, Archer, J, Arner, E, Arner, P, Babina, M, Baillie, K, Bajic, V, Baker, S, Balic, A, Balwierz, P, Beckhouse, A, Bertin, N, Blake, Ja, Blumenthal, A, Bodega, B, Bonetti, A, Briggs, J, Brombacher, F, Burroughs, M, Califano, A, Cannistraci, C, Carbajo, D, Carninci, P, Chen, Yang, Chierici, M, Ciani, Y, Clevers, H, Dalla, Emiliano, Daub, C, Davis, C, De Hoon, M, De Lima Morais, D, Dermar, M, Diehl, A, Dimont, E, Dohl, T, Drabros, F, Edge, A, Edinger, M, Ekwall, K, Endoh, M, Enomoto, H, Fagiolini, M, Fairbairn, L, Fang, H, Farach Carson, Mc, Faulkner, G, Favorov, A, Fisher, M, Forrest, A, Francescatto, M, Freeman, T, Frith, M, Fujita, R, Fukuda, S, Furlanello, C, Furuno, M, Furusawa, J, Geijtenbeek, Tb, Gibson, A, Gingeras, T, Goldowithz, D, Gough, J, Guhl, S, Guler, R, Gustincich, Stefano, Ha, T, Haberle, V, Hamaguchi, M, Hara, M, Harbers, M, Harshbarger, J, Hasegawa, A, Hasegawa, Y, Hashimoto, T, Hayashizaki, Y, Herlyn, M, Heutink, P, Hide, W, Hitchens, K, Ho Sui, S, Hofmann, O, Hoof, I, Hori, F, Hume, D, Huminiecki, L, Iida, K, Ikawa, T, Ishizu, Y, Itoh, M, Jankovic, B, Jia, H, Jorgensen, M, Joshi, A, Jurman, G, Kaczkowski, B, Kai, C, Kaida, K, Kaiho, A, Kajiyama, K, Kanamori Katayama, M, Kasianov, A, Kasukawa, T, Katayama, S, Kato Ishikawa, S, Kawaguchi, S, Kawai, J, Kawaji, H, Kawamoto, H, Kawamura, Y, Kawashima, T, Kempfle, J, Kenna, T, Kere, J, Khachigian, L, Kitamura, T, Klinken, P, Knox, A, Kojima, M, Kojima, S, Kondo, N, Koseki, H, Koyasu, S, Krampitz, S, Kubosaki, A, Kulakovskiy, I, Kwon, At, Laros, J, Lassmann, T, Lenhard, B, Lennartsson, A, Li, K, Lilji, B, Lipovich, L, Lizio, M, Mackay Sim, A, Makeev, V, Manabe, R, Mar, J, Marchand, B, Mathelier, A, Medvedeva, Y, Meehan, Tf, Mejhert, N, Meynert, A, Mizuno, Y, Morikawa, H, Morimoto, M, Moro, K, Motakis, E, Motohashi, H, Mummery, C, Mungall, Cj, Murata, M, Nagao Sato, S, Nakachi, Y, Nakahara, F, Nakamura, T, Nakamura, Y, Nakazato, K, Ninomiya Fukuda, N, Nishiyori Sueki, H, Noma, S, Nozaki, T, Ogishima, S, Ohkura, N, Ohmiya, H, Ohno, H, Ohshima, M, Okada Hatakeyama, M, Okazaki, Y, Orlando, V, Ovchinnikov, D, Pain, A, Passier, R, Persson, H, Piazza, Silvano, Plessy, C, Pradhan Bhatt, S, Prendergast, J, Rackham, O, Ramilowski, J, Rashid, M, Ravasi, T, Rehli, M, Rizzu, P, Roncador, M, Roy, S, Rye, M, Saijyo, E, Sajantila, A, Saka, A, Sakaguchi, S, Sakai, M, Sandelin, A, Sato, H, Satoh, H, Suzana, S, Alka, S, Schaefer, U, Schmeier, S, Schmidl, C, Schneider, C, Schultes, Ea, Schulze Tanzil, G, Schwegmann, A, Semple, C, Sengstag, T, Severin, J, Sheng, G, Shimoji, H, Shimoni, Y, Shin, J, Simon, C, Sugiyama, D, Sugiyama, T, Summers, K, Suzuki, H, Suzuki, M, Suzuki, N, Swoboda, R, Hoen P, T, Tagami, M, Takahashi, N, Takai, J, Tanaka, H, Tatsukawa, H, Tatum, Z, Taylor, M, Thompson, M, Toyoda, H, Toyoda, T, Valen, E, Van De Wetering, M, Van Den Berg, L, Van Nimwegen, E, Verardo, R, Vijayan, D, Vitezic, M, Vorontzov, I, Wasserman, W, Watanabe, S, Wells, C, Winteringham, L, Wolvetang, E, Wood, Ej, Yamaguchi, Y, Yamamoto, M, Yoneda, M, Yonekura, Y, Yoshida, Shin'Ichirou, Young, R, Zabierowski, Se, Zhang, P, Zhao, X, Zucchelli, Silvia, Forrest, Ar, Wagner, Gp, Hubrecht Institute for Developmental Biology and Stem Cell Research, AII - Amsterdam institute for Infection and Immunity, Infectious diseases, and Experimental Immunology

Subjects
Cell type, General Physics and Astronomy, rna-seq data, phylogenetic networks, Biology, ENCODE, General Biochemistry, Genetics and Molecular Biology, Divergence, Transcriptome, Models, Settore BIO/13 - Biologia Applicata, Neoplasms, Humans, Genetics, Models, Statistical, Multidisciplinary, Statistical model, General Chemistry, Statistical, Biological Evolution, Body plan, Tree structure, Evolutionary biology, Cancer cell
Abstract

In evolution, body plan complexity increases due to an increase in the number of individualized cell types. Yet, there is very little understanding of the mechanisms that produce this form of organismal complexity. One model for the origin of novel cell types is the sister cell-type model. According to this model, each cell type arises together with a sister cell type through specialization from an ancestral cell type. A key prediction of the sister cell-type model is that gene expression profiles of cell types exhibit tree structure. Here we present a statistical model for detecting tree structure in transcriptomic data and apply it to transcriptomes from ENCODE and FANTOM5. We show that transcriptomes of normal cells harbour substantial amounts of hierarchical structure. In contrast, cancer cell lines have less tree structure, suggesting that the emergence of cancer cells follows different principles from that of evolutionary cell-type origination.

Published
2015

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