Author: "Nakachi, Y." - Searchworks@Jio Institute Digital Library Search Results

Your search keyword '"Nakachi, Y."' showing total 85 results

Start Over Author "Nakachi, Y."

85 results on '"Nakachi, Y."'

1. Diagnosis and molecular basis of mitochondrial respiratory chain disorders: Exome sequencing for disease gene identification

Author: Ohtake, A., Murayama, K., Mori, M., Harashima, H., Yamazaki, T., Tamaru, S., Yamashita, Y., Kishita, Y., Nakachi, Y., Kohda, M., Tokuzawa, Y., Mizuno, Y., Moriyama, Y., Kato, H., and Okazaki, Y.
Published: 2014
Full Text: View/download PDF

2. Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

Author: Grapotte M., Saraswat M., Bessiere C., Menichelli C., Ramilowski J. A., Severin J., Hayashizaki Y., Itoh M., Tagami M., Murata M., Kojima-Ishiyama M., Noma S., Noguchi S., Kasukawa T., Hasegawa A., Suzuki H., Nishiyori-Sueki H., Frith M. C., Abugessaisa I., Aitken S., Aken B. L., Alam I., Alam T., Alasiri R., Alhendi A. M. N., Alinejad-Rokny H., Alvarez M. J., Andersson R., Arakawa T., Araki M., Arbel T., Archer J., Archibald A. L., Arner E., Arner P., Asai K., Ashoor H., Astrom G., Babina M., Baillie J. K., Bajic V. B., Bajpai A., Baker S., Baldarelli R. M., Balic A., Bansal M., Batagov A. O., Batzoglou S., Beckhouse A. G., Beltrami A. P., Beltrami C. A., Bertin N., Bhattacharya S., Bickel P. J., Blake J. A., Blanchette M., Bodega B., Bonetti A., Bono H., Bornholdt J., Bttcher M., Bougouffa S., Boyd M., Breda J., Brombacher F., Brown J. B., Bult C. J., Burroughs A. M., Burt D. W., Busch A., Caglio G., Califano A., Cameron C. J., Cannistraci C. V., Carbone A., Carlisle A. J., Carninci P., Carter K. W., Cesselli D., Chang J. -C., Chen J. C., Chen Y., Chierici M., Christodoulou J., Ciani Y., Clark E. L., Coskun M., Dalby M., Dalla E., Daub C. O., Davis C. A., de Hoon M. J. L., de Rie D., Denisenko E., Deplancke B., Detmar M., Deviatiiarov R., Di Bernardo D., Diehl A. D., Dieterich L. C., Dimont E., Djebali S., Dohi T., Dostie J., Drablos F., Edge A. S. B., Edinger M., Ehrlund A., Ekwall K., Elofsson A., Endoh M., Enomoto H., Enomoto S., Faghihi M., Fagiolini M., Farach-Carson M. C., Faulkner G. J., Favorov A., Fernandes A. M., Ferrai C., Forrest A. R. R., Forrester L. M., Forsberg M., Fort A., Francescatto M., Freeman T. C., Frith M., Fukuda S., Funayama M., Furlanello C., Furuno M., Furusawa C., Gao H., Gazova I., Gebhard C., Geier F., Geijtenbeek T. B. H., Ghosh S., Ghosheh Y., Gingeras T. R., Gojobori T., Goldberg T., Goldowitz D., Gough J., Greco D., Gruber A. J., Guhl S., Guigo R., Guler R., Gusev O., Gustincich S., Ha T. J., Haberle V., Hale P., Hallstrom B. M., Hamada M., Handoko L., Hara M., Harbers M., Harrow J., Harshbarger J., Hase T., Hashimoto K., Hatano T., Hattori N., Hayashi R., Herlyn M., Hettne K., Heutink P., Hide W., Hitchens K. J., Sui S. H., 't Hoen P. A. C., Hon C. C., Hori F., Horie M., Horimoto K., Horton P., Hou R., Huang E., Huang Y., Hugues R., Hume D., Ienasescu H., Iida K., Ikawa T., Ikemura T., Ikeo K., Inoue N., Ishizu Y., Ito Y., Ivshina A. V., Jankovic B. R., Jenjaroenpun P., Johnson R., Jorgensen M., Jorjani H., Joshi A., Jurman G., Kaczkowski B., Kai C., Kaida K., Kajiyama K., Kaliyaperumal R., Kaminuma E., Kanaya T., Kaneda H., Kapranov P., Kasianov A. S., Katayama T., Kato S., Kawaguchi S., Kawai J., Kawaji H., Kawamoto H., Kawamura Y. I., Kawasaki S., Kawashima T., Kempfle J. S., Kenna T. J., Kere J., Khachigian L., Kiryu H., Kishima M., Kitajima H., Kitamura T., Kitano H., Klaric E., Klepper K., Klinken S. P., Kloppmann E., Knox A. J., Kodama Y., Kogo Y., Kojima M., Kojima S., Komatsu N., Komiyama H., Kono T., Koseki H., Koyasu S., Kratz A., Kukalev A., Kulakovskiy I., Kundaje A., Kunikata H., Kuo R., Kuo T., Kuraku S., Kuznetsov V. A., Kwon T. J., Larouche M., Lassmann T., Law A., Le-Cao K. -A., Lecellier C. -H., Lee W., Lenhard B., Lennartsson A., Li K., Li R., Lilje B., Lipovich L., Lizio M., Lopez G., Magi S., Mak G. K., Makeev V., Manabe R., Mandai M., Mar J., Maruyama K., Maruyama T., Mason E., Mathelier A., Matsuda H., Medvedeva Y. A., Meehan T. F., Mejhert N., Meynert A., Mikami N., Minoda A., Miura H., Miyagi Y., Miyawaki A., Mizuno Y., Morikawa H., Morimoto M., Morioka M., Morishita S., Moro K., Motakis E., Motohashi H., Mukarram A. K., Mummery C. L., Mungall C. J., Murakawa Y., Muramatsu M., Nagasaka K., Nagase T., Nakachi Y., Nakahara F., Nakai K., Nakamura K., Nakamura Y., Nakazawa T., Nason G. P., Nepal C., Nguyen Q. H., Nielsen L. K., Nishida K., Nishiguchi K. M., Nishiyori H., Nitta K., Notredame C., Ogishima S., Ohkura N., Ohno H., Ohshima M., Ohtsu T., Okada Y., Okada-Hatakeyama M., Okazaki Y., Oksvold P., Orlando V., Ow G. S., Ozturk M., Pachkov M., Paparountas T., Parihar S. P., Park S. -J., Pascarella G., Passier R., Persson H., Philippens I. H., Piazza S., Plessy C., Pombo A., Ponten F., Poulain S., Poulsen T. M., Pradhan S., Prezioso C., Pridans C., Qin X. -Y., Quackenbush J., Rackham O., Ramilowski J., Ravasi T., Rehli M., Rennie S., Rito T., Rizzu P., Robert C., Roos M., Rost B., Roudnicky F., Roy R., Rye M. B., Sachenkova O., Saetrom P., Sai H., Saiki S., Saito M., Saito A., Sakaguchi S., Sakai M., Sakaue S., Sakaue-Sawano A., Sandelin A., Sano H., Sasamoto Y., Sato H., Saxena A., Saya H., Schafferhans A., Schmeier S., Schmidl C., Schmocker D., Schneider C., Schueler M., Schultes E. A., Schulze-Tanzil G., Semple C. A., Seno S., Seo W., Sese J., Sheng G., Shi J., Shimoni Y., Shin J. W., SimonSanchez J., Sivertsson A., Sjostedt E., Soderhall C., Laurent G. S., Stoiber M. H., Sugiyama D., Summers K. M., Suzuki A. M., Suzuki K., Suzuki M., Suzuki N., Suzuki T., Swanson D. J., Swoboda R. K., Taguchi A., Takahashi H., Takahashi M., Takamochi K., Takeda S., Takenaka Y., Tam K. T., Tanaka H., Tanaka R., Tanaka Y., Tang D., Taniuchi I., Tanzer A., Tarui H., Taylor M. S., Terada A., Terao Y., Testa A. C., Thomas M., Thongjuea S., Tomii K., Triglia E. T., Toyoda H., Tsang H. G., Tsujikawa M., Uhlen M., Valen E., van de Wetering M., van Nimwegen E., Velmeshev D., Verardo R., Vitezic M., Vitting-Seerup K., von Feilitzen K., Voolstra C. R., Vorontsov I. E., Wahlestedt C., Wasserman W. W., Watanabe K., Watanabe S., Wells C. A., Winteringham L. N., Wolvetang E., Yabukami H., Yagi K., Yamada T., Yamaguchi Y., Yamamoto M., Yamamoto Y., Yamanaka Y., Yano K., Yasuzawa K., Yatsuka Y., Yo M., Yokokura S., Yoneda M., Yoshida E., Yoshida Y., Yoshihara M., Young R., Young R. S., Yu N. Y., Yumoto N., Zabierowski S. E., Zhang P. G., Zucchelli S., Zwahlen M., Chatelain C., Brehelin L., Grapotte, M., Saraswat, M., Bessiere, C., Menichelli, C., Ramilowski, J. A., Severin, J., Hayashizaki, Y., Itoh, M., Tagami, M., Murata, M., Kojima-Ishiyama, M., Noma, S., Noguchi, S., Kasukawa, T., Hasegawa, A., Suzuki, H., Nishiyori-Sueki, H., Frith, M. C., Abugessaisa, I., Aitken, S., Aken, B. L., Alam, I., Alam, T., Alasiri, R., Alhendi, A. M. N., Alinejad-Rokny, H., Alvarez, M. J., Andersson, R., Arakawa, T., Araki, M., Arbel, T., Archer, J., Archibald, A. L., Arner, E., Arner, P., Asai, K., Ashoor, H., Astrom, G., Babina, M., Baillie, J. K., Bajic, V. B., Bajpai, A., Baker, S., Baldarelli, R. M., Balic, A., Bansal, M., Batagov, A. O., Batzoglou, S., Beckhouse, A. G., Beltrami, A. P., Beltrami, C. A., Bertin, N., Bhattacharya, S., Bickel, P. J., Blake, J. A., Blanchette, M., Bodega, B., Bonetti, A., Bono, H., Bornholdt, J., Bttcher, M., Bougouffa, S., Boyd, M., Breda, J., Brombacher, F., Brown, J. B., Bult, C. J., Burroughs, A. M., Burt, D. W., Busch, A., Caglio, G., Califano, A., Cameron, C. J., Cannistraci, C. V., Carbone, A., Carlisle, A. J., Carninci, P., Carter, K. W., Cesselli, D., Chang, J. -C., Chen, J. C., Chen, Y., Chierici, M., Christodoulou, J., Ciani, Y., Clark, E. L., Coskun, M., Dalby, M., Dalla, E., Daub, C. O., Davis, C. A., de Hoon, M. J. L., de Rie, D., Denisenko, E., Deplancke, B., Detmar, M., Deviatiiarov, R., Di Bernardo, D., Diehl, A. D., Dieterich, L. C., Dimont, E., Djebali, S., Dohi, T., Dostie, J., Drablos, F., Edge, A. S. B., Edinger, M., Ehrlund, A., Ekwall, K., Elofsson, A., Endoh, M., Enomoto, H., Enomoto, S., Faghihi, M., Fagiolini, M., Farach-Carson, M. C., Faulkner, G. J., Favorov, A., Fernandes, A. M., Ferrai, C., Forrest, A. R. R., Forrester, L. M., Forsberg, M., Fort, A., Francescatto, M., Freeman, T. C., Frith, M., Fukuda, S., Funayama, M., Furlanello, C., Furuno, M., Furusawa, C., Gao, H., Gazova, I., Gebhard, C., Geier, F., Geijtenbeek, T. B. H., Ghosh, S., Ghosheh, Y., Gingeras, T. R., Gojobori, T., Goldberg, T., Goldowitz, D., Gough, J., Greco, D., Gruber, A. J., Guhl, S., Guigo, R., Guler, R., Gusev, O., Gustincich, S., Ha, T. J., Haberle, V., Hale, P., Hallstrom, B. M., Hamada, M., Handoko, L., Hara, M., Harbers, M., Harrow, J., Harshbarger, J., Hase, T., Hashimoto, K., Hatano, T., Hattori, N., Hayashi, R., Herlyn, M., Hettne, K., Heutink, P., Hide, W., Hitchens, K. J., Sui, S. H., 't Hoen, P. A. C., Hon, C. C., Hori, F., Horie, M., Horimoto, K., Horton, P., Hou, R., Huang, E., Huang, Y., Hugues, R., Hume, D., Ienasescu, H., Iida, K., Ikawa, T., Ikemura, T., Ikeo, K., Inoue, N., Ishizu, Y., Ito, Y., Ivshina, A. V., Jankovic, B. R., Jenjaroenpun, P., Johnson, R., Jorgensen, M., Jorjani, H., Joshi, A., Jurman, G., Kaczkowski, B., Kai, C., Kaida, K., Kajiyama, K., Kaliyaperumal, R., Kaminuma, E., Kanaya, T., Kaneda, H., Kapranov, P., Kasianov, A. S., Katayama, T., Kato, S., Kawaguchi, S., Kawai, J., Kawaji, H., Kawamoto, H., Kawamura, Y. I., Kawasaki, S., Kawashima, T., Kempfle, J. S., Kenna, T. J., Kere, J., Khachigian, L., Kiryu, H., Kishima, M., Kitajima, H., Kitamura, T., Kitano, H., Klaric, E., Klepper, K., Klinken, S. P., Kloppmann, E., Knox, A. J., Kodama, Y., Kogo, Y., Kojima, M., Kojima, S., Komatsu, N., Komiyama, H., Kono, T., Koseki, H., Koyasu, S., Kratz, A., Kukalev, A., Kulakovskiy, I., Kundaje, A., Kunikata, H., Kuo, R., Kuo, T., Kuraku, S., Kuznetsov, V. A., Kwon, T. J., Larouche, M., Lassmann, T., Law, A., Le-Cao, K. -A., Lecellier, C. -H., Lee, W., Lenhard, B., Lennartsson, A., Li, K., Li, R., Lilje, B., Lipovich, L., Lizio, M., Lopez, G., Magi, S., Mak, G. K., Makeev, V., Manabe, R., Mandai, M., Mar, J., Maruyama, K., Maruyama, T., Mason, E., Mathelier, A., Matsuda, H., Medvedeva, Y. A., Meehan, T. F., Mejhert, N., Meynert, A., Mikami, N., Minoda, A., Miura, H., Miyagi, Y., Miyawaki, A., Mizuno, Y., Morikawa, H., Morimoto, M., Morioka, M., Morishita, S., Moro, K., Motakis, E., Motohashi, H., Mukarram, A. K., Mummery, C. L., Mungall, C. J., Murakawa, Y., Muramatsu, M., Nagasaka, K., Nagase, T., Nakachi, Y., Nakahara, F., Nakai, K., Nakamura, K., Nakamura, Y., Nakazawa, T., Nason, G. P., Nepal, C., Nguyen, Q. H., Nielsen, L. K., Nishida, K., Nishiguchi, K. M., Nishiyori, H., Nitta, K., Notredame, C., Ogishima, S., Ohkura, N., Ohno, H., Ohshima, M., Ohtsu, T., Okada, Y., Okada-Hatakeyama, M., Okazaki, Y., Oksvold, P., Orlando, V., Ow, G. S., Ozturk, M., Pachkov, M., Paparountas, T., Parihar, S. P., Park, S. -J., Pascarella, G., Passier, R., Persson, H., Philippens, I. H., Piazza, S., Plessy, C., Pombo, A., Ponten, F., Poulain, S., Poulsen, T. M., Pradhan, S., Prezioso, C., Pridans, C., Qin, X. -Y., Quackenbush, J., Rackham, O., Ramilowski, J., Ravasi, T., Rehli, M., Rennie, S., Rito, T., Rizzu, P., Robert, C., Roos, M., Rost, B., Roudnicky, F., Roy, R., Rye, M. B., Sachenkova, O., Saetrom, P., Sai, H., Saiki, S., Saito, M., Saito, A., Sakaguchi, S., Sakai, M., Sakaue, S., Sakaue-Sawano, A., Sandelin, A., Sano, H., Sasamoto, Y., Sato, H., Saxena, A., Saya, H., Schafferhans, A., Schmeier, S., Schmidl, C., Schmocker, D., Schneider, C., Schueler, M., Schultes, E. A., Schulze-Tanzil, G., Semple, C. A., Seno, S., Seo, W., Sese, J., Sheng, G., Shi, J., Shimoni, Y., Shin, J. W., Simonsanchez, J., Sivertsson, A., Sjostedt, E., Soderhall, C., Laurent, G. S., Stoiber, M. H., Sugiyama, D., Summers, K. M., Suzuki, A. M., Suzuki, K., Suzuki, M., Suzuki, N., Suzuki, T., Swanson, D. J., Swoboda, R. K., Taguchi, A., Takahashi, H., Takahashi, M., Takamochi, K., Takeda, S., Takenaka, Y., Tam, K. T., Tanaka, H., Tanaka, R., Tanaka, Y., Tang, D., Taniuchi, I., Tanzer, A., Tarui, H., Taylor, M. S., Terada, A., Terao, Y., Testa, A. C., Thomas, M., Thongjuea, S., Tomii, K., Triglia, E. T., Toyoda, H., Tsang, H. G., Tsujikawa, M., Uhlen, M., Valen, E., van de Wetering, M., van Nimwegen, E., Velmeshev, D., Verardo, R., Vitezic, M., Vitting-Seerup, K., von Feilitzen, K., Voolstra, C. R., Vorontsov, I. E., Wahlestedt, C., Wasserman, W. W., Watanabe, K., Watanabe, S., Wells, C. A., Winteringham, L. N., Wolvetang, E., Yabukami, H., Yagi, K., Yamada, T., Yamaguchi, Y., Yamamoto, M., Yamamoto, Y., Yamanaka, Y., Yano, K., Yasuzawa, K., Yatsuka, Y., Yo, M., Yokokura, S., Yoneda, M., Yoshida, E., Yoshida, Y., Yoshihara, M., Young, R., Young, R. S., Yu, N. Y., Yumoto, N., Zabierowski, S. E., Zhang, P. G., Zucchelli, S., Zwahlen, M., Chatelain, C., Brehelin, L., Institute of Biotechnology, Biosciences, Institut de Génétique Moléculaire de Montpellier (IGMM), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Institut de Biologie Computationnelle (IBC), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Méthodes et Algorithmes pour la Bioinformatique (MAB), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), RIKEN Center for Integrative Medical Sciences [Yokohama] (RIKEN IMS), RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN), National Institute of Advanced Industrial Science and Technology (AIST), SANOFI Recherche, University of British Columbia (UBC), Experimental Immunology, Infectious diseases, AII - Infectious diseases, Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), and Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Montpellier (UM)
Subjects: 0301 basic medicine, General Physics and Astronomy, Genome, Mice, 0302 clinical medicine, Transcription (biology), Promoter Regions, Genetic, Transcription Initiation, Genetic, 0303 health sciences, Multidisciplinary, 1184 Genetics, developmental biology, physiology, High-Throughput Nucleotide Sequencing, Neurodegenerative Diseases, 222 Other engineering and technologies, Genomics, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], humanities, Enhancer Elements, Genetic, Microsatellite Repeat, Transcription Initiation Site, Sequence motif, Transcription Initiation, Human, Enhancer Elements, Neural Networks, Science, 610 Medicine & health, Computational biology, Biology, Article, General Biochemistry, Genetics and Molecular Biology, Promoter Regions, 03 medical and health sciences, Computer, Deep Learning, Tandem repeat, Genetic, Clinical Research, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], Machine learning, Genetics, Animals, Humans, Polymorphism, Enhancer, Transcriptomics, Gene, A549 Cell, 030304 developmental biology, Polymorphism, Genetic, Neurodegenerative Disease, Base Sequence, Animal, Genome, Human, Human Genome, Computational Biology, Promoter, General Chemistry, 113 Computer and information sciences, Cap analysis gene expression, 030104 developmental biology, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, Cardiovascular and Metabolic Diseases, A549 Cells, Minion, Generic health relevance, 3111 Biomedicine, Neural Networks, Computer, 610 Medizin und Gesundheit, 030217 neurology & neurosurgery, FANTOM consortium, Microsatellite Repeats
Abstract: Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism., Nature Communications, 12 (1), ISSN:2041-1723
Published: 2020
Full Text: View/download PDF

3. Gait speed is a strong predictor of the ability to walk independently without wheelchair assistance in a facility setting for post-stroke patients

Author: Yamada, R., primary, Ichinosawa, Y., additional, Shimizu, S., additional, Takemura, N., additional, Taira, K., additional, Goya, M., additional, Nakachi, Y., additional, Onodera, A., additional, Nakanishi, T., additional, and Matsunaga, A., additional
Published: 2018
Full Text: View/download PDF

4. FRI0079 TAS5315, a novel bruton's tyrosine kinase inhibitor, improve bone mineral density (BMD) and bone erosion via inhibition of osteoclast activation in murine model for rheumatoid arthritis

Author: Yoshiga, Y, primary, Hosoi, F, additional, Iguchi, S, additional, Kaneko, R, additional, Nakachi, Y, additional, Akasaka, D, additional, Tanaka, K, additional, Yonekura, K, additional, Utsugi, T, additional, Sasaki, E, additional, and Iwasawa, Y, additional
Published: 2017
Full Text: View/download PDF

5. Data Descriptor: FANTOM5 CAGE profiles of human and mouse samples

Author: Noguchi, S, Arakawa, T, Fukuda, S, Furuno, M, Hasegawa, A, Hori, F, Ishikawa-Kato, S, Kaida, K, Kaiho, A, Kanamori-Katayama, M, Kawashima, T, Kojima, M, Kubosaki, A, Manabe, R-I, Murata, M, Nagao-Sato, S, Nakazato, K, Ninomiya, N, Nishiyori-Sueki, H, Noma, S, Saijyo, E, Saka, A, Sakai, M, Simon, C, Suzuki, N, Tagami, M, Watanabe, S, Yoshida, S, Arner, P, Axton, RA, Babina, M, Baillie, JK, Barnett, TC, Beckhouse, AG, Blumenthal, A, Bodega, B, Bonetti, A, Briggs, J, Brombacher, F, Carlisle, AJ, Clevers, HC, Davis, CA, Detmar, M, Dohi, T, Edge, ASB, Edinger, M, Ehrlund, A, Ekwall, K, Endoh, M, Enomoto, H, Eslami, A, Fagiolini, M, Fairbairn, L, Farach-Carson, MC, Faulkner, GJ, Ferrai, C, Fisher, ME, Forrester, LM, Fujita, R, Furusawa, J-I, Geijtenbeek, TB, Gingeras, T, Goldowitz, D, Guhl, S, Guler, R, Gustincich, S, Ha, TJ, Hamaguchi, M, Hara, M, Hasegawa, Y, Herlyn, M, Heutink, P, Hitchens, KJ, Hume, DA, Ikawa, T, Ishizu, Y, Kai, C, Kawamoto, H, Kawamura, YI, Kempfle, JS, Kenna, TJ, Kere, J, Khachigian, LM, Kitamura, T, Klein, S, Klinken, SP, Knox, AJ, Kojima, S, Koseki, H, Koyasu, S, Lee, W, Lennartsson, A, Mackay-sim, A, Mejhert, N, Mizuno, Y, Morikawa, H, Morimoto, M, Moro, K, Morris, KJ, Motohashi, H, Mummery, CL, Nakachi, Y, Nakahara, F, Nakamura, T, Nakamura, Y, Nozaki, T, Ogishima, S, Ohkura, N, Ohno, H, Ohshima, M, Okada-Hatakeyama, M, Okazaki, Y, Orlando, V, Ovchinnikov, DA, Passier, R, Patrikakis, M, Pombo, A, Pradhan-Bhatt, S, Qin, X-Y, Rehli, M, Rizzu, P, Roy, S, Sajantila, A, Sakaguchi, S, Sato, H, Satoh, H, Savvi, S, Saxena, A, Schmidl, C, Schneider, C, Schulze-Tanzil, GG, Schwegmann, A, Sheng, G, Shin, JW, Sugiyama, D, Sugiyama, T, Summers, KM, Takahashi, N, Takai, J, Tanaka, H, Tatsukawa, H, Tomoiu, A, Toyoda, H, van de Wetering, M, van den Berg, LM, Verardo, R, Vijayan, D, Wells, CA, Winteringham, LN, Wolvetang, E, Yamaguchi, Y, Yamamoto, M, Yanagi-Mizuochi, C, Yoneda, M, Yonekura, Y, Zhang, PG, Zucchelli, S, Abugessaisa, I, Arner, E, Harshbarger, J, Kondo, A, Lassmann, T, Lizio, M, Sahin, S, Sengstag, T, Severin, J, Shimoji, H, Suzuki, M, Suzuki, H, Kawai, J, Kondo, N, Itoh, M, Daub, CO, Kasukawa, T, Kawaji, H, Carninci, P, Forrest, ARR, Hayashizaki, Y, Noguchi, S, Arakawa, T, Fukuda, S, Furuno, M, Hasegawa, A, Hori, F, Ishikawa-Kato, S, Kaida, K, Kaiho, A, Kanamori-Katayama, M, Kawashima, T, Kojima, M, Kubosaki, A, Manabe, R-I, Murata, M, Nagao-Sato, S, Nakazato, K, Ninomiya, N, Nishiyori-Sueki, H, Noma, S, Saijyo, E, Saka, A, Sakai, M, Simon, C, Suzuki, N, Tagami, M, Watanabe, S, Yoshida, S, Arner, P, Axton, RA, Babina, M, Baillie, JK, Barnett, TC, Beckhouse, AG, Blumenthal, A, Bodega, B, Bonetti, A, Briggs, J, Brombacher, F, Carlisle, AJ, Clevers, HC, Davis, CA, Detmar, M, Dohi, T, Edge, ASB, Edinger, M, Ehrlund, A, Ekwall, K, Endoh, M, Enomoto, H, Eslami, A, Fagiolini, M, Fairbairn, L, Farach-Carson, MC, Faulkner, GJ, Ferrai, C, Fisher, ME, Forrester, LM, Fujita, R, Furusawa, J-I, Geijtenbeek, TB, Gingeras, T, Goldowitz, D, Guhl, S, Guler, R, Gustincich, S, Ha, TJ, Hamaguchi, M, Hara, M, Hasegawa, Y, Herlyn, M, Heutink, P, Hitchens, KJ, Hume, DA, Ikawa, T, Ishizu, Y, Kai, C, Kawamoto, H, Kawamura, YI, Kempfle, JS, Kenna, TJ, Kere, J, Khachigian, LM, Kitamura, T, Klein, S, Klinken, SP, Knox, AJ, Kojima, S, Koseki, H, Koyasu, S, Lee, W, Lennartsson, A, Mackay-sim, A, Mejhert, N, Mizuno, Y, Morikawa, H, Morimoto, M, Moro, K, Morris, KJ, Motohashi, H, Mummery, CL, Nakachi, Y, Nakahara, F, Nakamura, T, Nakamura, Y, Nozaki, T, Ogishima, S, Ohkura, N, Ohno, H, Ohshima, M, Okada-Hatakeyama, M, Okazaki, Y, Orlando, V, Ovchinnikov, DA, Passier, R, Patrikakis, M, Pombo, A, Pradhan-Bhatt, S, Qin, X-Y, Rehli, M, Rizzu, P, Roy, S, Sajantila, A, Sakaguchi, S, Sato, H, Satoh, H, Savvi, S, Saxena, A, Schmidl, C, Schneider, C, Schulze-Tanzil, GG, Schwegmann, A, Sheng, G, Shin, JW, Sugiyama, D, Sugiyama, T, Summers, KM, Takahashi, N, Takai, J, Tanaka, H, Tatsukawa, H, Tomoiu, A, Toyoda, H, van de Wetering, M, van den Berg, LM, Verardo, R, Vijayan, D, Wells, CA, Winteringham, LN, Wolvetang, E, Yamaguchi, Y, Yamamoto, M, Yanagi-Mizuochi, C, Yoneda, M, Yonekura, Y, Zhang, PG, Zucchelli, S, Abugessaisa, I, Arner, E, Harshbarger, J, Kondo, A, Lassmann, T, Lizio, M, Sahin, S, Sengstag, T, Severin, J, Shimoji, H, Suzuki, M, Suzuki, H, Kawai, J, Kondo, N, Itoh, M, Daub, CO, Kasukawa, T, Kawaji, H, Carninci, P, Forrest, ARR, and Hayashizaki, Y
Abstract: In the FANTOM5 project, transcription initiation events across the human and mouse genomes were mapped at a single base-pair resolution and their frequencies were monitored by CAGE (Cap Analysis of Gene Expression) coupled with single-molecule sequencing. Approximately three thousands of samples, consisting of a variety of primary cells, tissues, cell lines, and time series samples during cell activation and development, were subjected to a uniform pipeline of CAGE data production. The analysis pipeline started by measuring RNA extracts to assess their quality, and continued to CAGE library production by using a robotic or a manual workflow, single molecule sequencing, and computational processing to generate frequencies of transcription initiation. Resulting data represents the consequence of transcriptional regulation in each analyzed state of mammalian cells. Non-overlapping peaks over the CAGE profiles, approximately 200,000 and 150,000 peaks for the human and mouse genomes, were identified and annotated to provide precise location of known promoters as well as novel ones, and to quantify their activities.
Published: 2017

6. 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
Full Text: View/download PDF

7. Differential roles of epigenetic changes and Foxp3 expression in regulatory T cell-specific transcriptional regulation

Author: Morikawa, H, Ohkura, N, Vandenbon, A, Itoh, M, Nagao Sato, S, Kawaji, H, Lassmann, T, Carninci, P, Hayashizaki, Y, Forrest, Ar, Standley, Dm, Date, H, Sakaguchi, S, FANTOM Consortium (Forrest AR, Rehli, M, Baillie, Jk, de Hoon MJ, Haberle, V, Kulakovskiy, Iv, Lizio, 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, Ca, Ishizu, Y, Francescatto, M, Alam, I, Albanese, D, Altschuler, Gm, Archer, Ja, Arner, P, Babina, M, Baker, 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, Deplancke, B, 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, Furuno, M, Furusawa, J, Geijtenbeek, Tb, Gibson, A, Gingeras, T, Goldowitz, D, Gough, J, Guhl, S, Guler, R, Gustincich, Stefano, 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, Morais, Da, Morimoto, M, Moro, K, Motakis, E, Motohashi, H, Mummery, Cl, Murata, M, Nakachi, Y, Nakahara, F, Nakamura, T, Nakamura, Y, Nakazato, K, van Nimwegen, E, Ninomiya, N, Nishiyori, H, Noma, S, Nozaki, T, Ogishima, S, Ohmiya, 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, Sakai, M, Sato, H, Satoh, 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, Swoboda, Rk, 't Hoen PA, Tagami, M, Takahashi, N, Takai, J, Tanaka, H, Tatsukawa, H, Tatum, Z, Thompson, M, Toyoda, H, Toyoda, T, Valen, E, van de Wetering, M, van den Berg LM, Verardo, 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, Hayashizaki, Y., AII - Amsterdam institute for Infection and Immunity, Infectious diseases, Experimental Immunology, and Hubrecht Institute for Developmental Biology and Stem Cell Research
Subjects: Transcription, Genetic, Regulatory T cell, T-Lymphocytes, Down-Regulation, chemical and pharmacologic phenomena, Biology, Inbred C57BL, T-Lymphocytes, Regulatory, Epigenesis, Genetic, Mice, Genetic, Settore BIO/13 - Biologia Applicata, medicine, Transcriptional regulation, Animals, Epigenetics, Gene, Inbred BALB C, Genetics, Regulation of gene expression, Mice, Inbred BALB C, Multidisciplinary, Binding Sites, FOXP3, hemic and immune systems, Forkhead Transcription Factors, DNA Methylation, Biological Sciences, Regulatory, Cap analysis gene expression, Mice, Inbred C57BL, medicine.anatomical_structure, Gene Expression Regulation, DNA methylation, Transcription, Epigenesis
Abstract: Naturally occurring regulatory T (Treg) cells, which specifically express the transcription factor forkhead box P3 (Foxp3), are engaged in the maintenance of immunological self-tolerance and homeostasis. By transcriptional start site cluster analysis, we assessed here how genome-wide patterns of DNA methylation or Foxp3 binding sites were associated with Treg-specific gene expression. We found that Treg-specific DNA hypomethylated regions were closely associated with Treg up-regulated transcriptional start site clusters, whereas Foxp3 binding regions had no significant correlation with either up- or down-regulated clusters in nonactivated Treg cells. However, in activated Treg cells, Foxp3 binding regions showed a strong correlation with down-regulated clusters. In accordance with these findings, the above two features of activation-dependent gene regulation in Treg cells tend to occur at different locations in the genome. The results collectively indicate that Treg-specific DNA hypomethylation is instrumental in gene up-regulation in steady state Treg cells, whereas Foxp3 down-regulates the expression of its target genes in activated Treg cells. Thus, the two events seem to play distinct but complementary roles in Treg-specific gene expression.
Published: 2014
Full Text: View/download PDF

8. OP0075 TAS5315, A Novel Bruton's Tyrosine Kinase (BTK) Inhibitor, Demonstrates Potent Efficacy in Mouse Collagen-Induced Arthritis Model

Author: Hosoi, F., primary, Iguchi, S., additional, Yoshiga, Y., additional, Kaneko, R., additional, Nakachi, Y., additional, Akasaka, D., additional, Yonekura, K., additional, Iwasawa, Y., additional, Sasaki, E., additional, and Utsugi, T., additional
Published: 2015
Full Text: View/download PDF

9. Fast optimization method for service restoration in sub-transmission systems with priority loads

Author: Watanabe, I., primary, Takehara, A., additional, Nakachi, Y., additional, and Verma, S.C., additional
Published: 2009
Full Text: View/download PDF

10. Probabilistic Evaluation Method of Available Transfer Capability Considering Reliability Margins in Transmission Network

Author: Sekita, K., primary, Yokoyama, A., additional, Verma, S.C., additional, and Nakachi, Y., additional
Published: 2008
Full Text: View/download PDF

11. A multi-agent cooperative voltage control method

Author: Nagata, T., primary, Nakachi, Y., additional, and Hatano, R., additional
Published: 2008
Full Text: View/download PDF

12. Calculation of transformer saturated leakage inductance based on field test data

Author: Nakachi, Y., primary, Hatano, R., additional, Matsubara, T., additional, and Uemura, Y., additional
Published: 2006
Full Text: View/download PDF

13. An optimal power flow control method of power system by interline power flow controller (IPFC)

Author: Tecrathana, S., primary, Yokoyama, A., additional, Nakachi, Y., additional, and Yasumatsu, M., additional
Published: 2005
Full Text: View/download PDF

14. Voltage / Reactive Power Control Optimization with Economy and Security using Tabu Search.

Author: Nakachi, Y., Kato, A., and Ukai, H.
Published: 2007
Full Text: View/download PDF

15. A Hybrid Genetic Algorithm for Service Restoration Problems in Power Distribution Systems.

Author: Watanabe, I., Kurihara, I., and Nakachi, Y.
Published: 2006
Full Text: View/download PDF

16. Implementation of unified power flow controller and verification for transmission capability improvement

Author: Morioka, Y., primary, Kato, M., additional, Mishima, Y., additional, Nakachi, Y., additional, Asada, M., additional, and Tokuhara, K., additional
Published: 1999
Full Text: View/download PDF

17. Nucleotide compositional constraints on genomes generate alanine-, glycine-, and proline-rich structures in transcription factors

Author: Nakachi, Y., primary, Hayakawa, T., additional, Oota, H., additional, Sumiyama, K., additional, Wang, L., additional, and Ueda, S., additional
Published: 1997
Full Text: View/download PDF

18. Application Of Digital Signal Processor For High Speed Scientific Calculation.

Author: Nakachi, Y., Mitsui, H., iijima, N., Sone, M., and Yoshida, Y.
Published: 1992
Full Text: View/download PDF

19. Digital Signal Processor - Pipe Line Feature In Power System Analysis With Band Matrix.

Author: Verma, S.C., Nakamura, K., Naito, K., Minami, Y., Sone, M., Nakachi, Y., and Fujita, H.
Published: 1993
Full Text: View/download PDF

20. Analysis of gene networks during adipogenesis and osteoblastgenesis focusing on the crosstalk and redundant pathways

Author: Bono, H., Yagi, K., Nakachi, Y., Nikaido, I., and Yasushi Okazaki

21. Simulation study of power quality compensation system using EDLC for distribution systems

Author: Konishi, H., primary, Sugimoto, S., additional, Nakachi, Y., additional, and Ogawa, S., additional
Full Text: View/download PDF

22. Application Of Digital Signal Processor For High Speed Scientific Calculation

Author: Nakachi, Y., primary, Mitsui, H., additional, iijima, N., additional, Sone, M., additional, and Yoshida, Y., additional
Full Text: View/download PDF

23. Digital Signal Processor - Pipe Line Feature In Power System Analysis With Band Matrix

Author: Verma, S.C., primary, Nakamura, K., additional, Naito, K., additional, Minami, Y., additional, Sone, M., additional, Nakachi, Y., additional, and Fujita, H., additional
Full Text: View/download PDF

24. A Hybrid Genetic Algorithm for Service Restoration Problems in Power Distribution Systems

Author: Watanabe, I., primary, Kurihara, I., additional, and Nakachi, Y., additional
Full Text: View/download PDF

25. Simulation study of power quality compensation system using EDLC for distribution systems.

Author: Konishi, H., Sugimoto, S., Nakachi, Y., and Ogawa, S.
Published: 2002
Full Text: View/download PDF

26. Development of a method for the imputation of the multi-allelic serotonin-transporter-linked polymorphic region (5-HTTLPR) in the Japanese population.

Author: Yanagida Y, Naka I, Nakachi Y, Ikegame T, Kasai K, Kajitani N, Takebayashi M, Bundo M, Ohashi J, and Iwamoto K
Subjects: Humans, East Asian People genetics, Gene Frequency, Genotype, Japan epidemiology, Alleles, Polymorphism, Single Nucleotide, Serotonin Plasma Membrane Transport Proteins genetics
Abstract: Serotonin-transporter-linked polymorphic region (5-HTTLPR), a variable number of tandem repeats in the promoter region of serotonin transporter gene, is classified into short (S) and long (L) alleles. Initial case-control association studies claiming the risks of the S allele in depression and anxiety were not completely supported by recent studies. However, most studies, especially those on East Asian populations, have overlooked the complexity of 5-HTTLPR, which involves multiple different alleles with distinct functional properties. To address this issue, distinguishing multiple 5-HTTLPR alleles is essential. Here, using the 5-HTTLPR genotypes previously determined by exhaustive Sanger sequencing of approximately 1,500 Japanese subjects and their comprehensive SNP data, we constructed a method for 5-HTTLPR genotype imputation. We identified 28 tag SNPs for the imputation of four major 5-HTTLPR alleles, which collectively account for 97.6% of 5-HTTLPR alleles in the Japanese population. Our imputation method, achieved an accuracy of 0.872 in cross-validation, will contribute to association analysis of 5-HTTLPR in the Japanese subjects., Competing Interests: Competing interests: Some of the authors declared financial and non-financial relationships and activities, and conflicts of interest regarding this manuscript as indicated in the supplementary materials. The sponsor had no role in study design, data collection, data analysis, data interpretation or writing of the report., (© 2024. The Author(s), under exclusive licence to The Japan Society of Human Genetics.)
Published: 2025
Full Text: View/download PDF

27. Exploration of cell type-specific somatic mutations in schizophrenia and the impact of maternal immune activation on the somatic mutation profile in the brain.

Author: Du J, Nakachi Y, Murata Y, Kiyota E, Kato T, Bundo M, and Iwamoto K
Subjects: Humans, Mice, Animals, Brain metabolism, Prefrontal Cortex metabolism, Neurons metabolism, Mutation, Schizophrenia metabolism
Abstract: Aim: Schizophrenia (SZ) is a severe psychiatric disorder caused by the interaction of genetic and environmental factors. Although somatic mutations that occur in the brain after fertilization may play an important role in the cause of SZ, their frequencies and patterns in the brains of patients and related animal models have not been well studied. This study aimed to find somatic mutations related to the pathophysiology of SZ., Methods: We performed whole-exome sequencing (WES) of neuronal and nonneuronal nuclei isolated from the postmortem prefrontal cortex of patients with SZ (n = 10) and controls (n = 10). After detecting somatic mutations, we explored the similarities and differences in shared common mutations between two cell types and cell type-specific mutations. We also performed WES of prefrontal cortex samples from an animal model of SZ based on maternal immune activation (MIA) and explored the possible impact of MIA on the patterns of somatic mutations., Results: We did not find quantitative differences in somatic mutations but found higher variant allele fractions of neuron-specific mutations in patients with SZ. In the mouse model, we found a larger variation in the number of somatic mutations in the offspring of MIA mice, with the occurrence of somatic mutations in neurodevelopment-related genes., Conclusion: Somatic mutations occurring at an earlier stage of brain cell differentiation toward neurons may be important for the cause of SZ. MIA may affect somatic mutation profiles in the brain., (© 2024 The Authors. Psychiatry and Clinical Neurosciences © 2024 Japanese Society of Psychiatry and Neurology.)
Published: 2024
Full Text: View/download PDF

28. Quantification of cytosine modifications in the aged mouse brain.

Author: Sugawara H, Date A, Fuke S, Nakachi Y, Kato T, Narita M, Bundo M, and Iwamoto K
Subjects: Animals, Mice, 5-Methylcytosine metabolism, Brain metabolism, Cerebellum metabolism, Epigenesis, Genetic, Cytosine metabolism
Abstract: Quantifying cytosine modifications in various brain regions provides important insights into the gene expression regulation and pathophysiology of neuropsychiatric disorders. In this study, we quantified 5-methylcytosine (5-mC), 5-hydroxymethylation (5-hmC), and 5-formylcytosine (5-fC) levels in five brain regions (the frontal lobe, cerebral cortical region without frontal lobe, hippocampus, basal ganglia, and the cerebellum) and the heart at three developmental periods (12, 48, and 101 weeks). We observed significant regional variations in cytosine modification. Notably, regional variations were generally maintained throughout development, suggesting that epigenetic regulation is unique to each brain region and remains relatively stable with age. The 5-mC and 5-hmC levels were positively correlated, although the extent of the correlations seemed to differ in different brain regions. On the contrary, 5-fC levels did not correlate with 5-mC or 5-hmC levels. Additionally, we observed an age-dependent decrease in 5-fC levels in the basal ganglia, suggesting a unique epigenetic regulation mechanism. Further high-resolution studies using animal models of neuropsychiatric disorders as well as postmortem brain evaluation are warranted., (© 2023 The Authors. Neuropsychopharmacology Reports published by John Wiley & Sons Australia, Ltd on behalf of The Japanese Society of Neuropsychopharmacology.)
Published: 2024
Full Text: View/download PDF

29. LINE-1 hypomethylation, increased retrotransposition and tumor-specific insertion in upper gastrointestinal cancer.

Author: Baba Y, Yasuda N, Bundo M, Nakachi Y, Ueda J, Ishimoto T, Iwatsuki M, Miyamoto Y, Yoshida N, Oshiumi H, Iwamoto K, and Baba H
Subjects: Humans, DNA Methylation genetics, Long Interspersed Nucleotide Elements genetics, Esophagus, Gastrointestinal Neoplasms genetics, Stomach Neoplasms genetics
Abstract: The long interspersed nuclear element-1 (LINE-1) retrotransposons are a major family of mobile genetic elements, comprising approximately 17% of the human genome. The methylation state of LINE-1 is often used as an indicator of global DNA methylation levels and it regulates the retrotransposition and somatic insertion of the genetic element. We have previously reported the significant relationship between LINE-1 hypomethylation and poor prognosis in upper gastrointestinal (GI) cancers. However, the causal relationships between LINE-1 hypomethylation, retrotransposition, and tumor-specific insertion in upper GI cancers remain unknown. We used bisulfite-pyrosequencing and quantitative real-time PCR to verify LINE-1 methylation and copy number in tissue samples of 101 patients with esophageal and 103 patients with gastric cancer. Furthermore, we analyzed the LINE-1 retrotransposition profile with an originally developed L1Hs-seq. In tumor samples, LINE-1 methylation levels were significantly lower than non-tumor controls, while LINE-1 copy numbers were markedly increased. As such, there was a significant inverse correlation between the LINE-1 methylation level and copy number in tumor tissues, with lower LINE-1 methylation levels corresponding to higher LINE-1 copy numbers. Of particular importance is that somatic LINE-1 insertions were more numerous in tumor than normal tissues. Furthermore, we observed that LINE-1 was inserted evenly across all chromosomes, and most often within genomic regions associated with tumor-suppressive genes. LINE-1 hypomethylation in upper GI cancers is related to increased LINE-1 retrotransposition and tumor-specific insertion events, which may collectively contribute to the acquisition of aggressive tumor features through the inactivation of tumor-suppressive genes., (© 2023 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.)
Published: 2024
Full Text: View/download PDF

30. Identification of epigenetically active L1 promoters in the human brain and their relationship with psychiatric disorders.

Author: Watanabe R, Nakachi Y, Matsubara H, Ueda J, Ishii T, Ukai W, Hashimoto E, Kasai K, Simizu S, Kato T, Bundo M, and Iwamoto K
Subjects: Humans, 5' Untranslated Regions, Long Interspersed Nucleotide Elements genetics, Brain, Epigenesis, Genetic, Mental Disorders genetics
Abstract: Long interspersed nuclear element-1 (LINE-1, L1) affects the transcriptome landscape in multiple ways. Promoter activity within its 5'UTR plays a critical role in regulating diverse L1 activities. However, the epigenetic status of L1 promoters in adult brain cells and their relationship with psychiatric disorders remain poorly understood. Here, we examined DNA methylation and hydroxymethylation of the full-length L1s in neurons and nonneurons and identified "epigenetically active" L1s. Notably, some of epigenetically active L1s were retrotransposition competent, which even had chimeric transcripts from the antisense promoters at their 5'UTRs. We also identified differentially methylated L1s in the prefrontal cortices of patients with psychiatric disorders. In nonneurons of bipolar disorder patients, one L1 was significantly hypomethylated and showed an inverse correlation with the expression level of the overlapping gene NREP. Finally, we observed that altered DNA methylation levels of L1 in patients with psychiatric disorders were not affected by the surrounding genomic regions but originated from the L1 sequences. These results suggested that altered epigenetic regulation of the L1 5'UTR in the brain was involved in the pathophysiology of psychiatric disorders., Competing Interests: Conflict of Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Elsevier Ltd and Japan Neuroscience Society. All rights reserved.)
Published: 2023
Full Text: View/download PDF

31. Sex-dependent behavioral alterations in a poly(I:C)-induced maternal immune activation mouse model without segment filamentous bacteria.

Author: Fujii S, Murata Y, Imamura Y, Nakachi Y, Bundo M, Kubota-Sakashita M, Kato T, and Iwamoto K
Subjects: Humans, Mice, Adult, Animals, Female, Male, Mice, Inbred C57BL, Disease Models, Animal, Cytoskeleton, Poly I-C pharmacology, Bacteria
Abstract: Maternal immune activation is one of the environmental risk factors for offspring to develop psychiatric disorders. A synthetic viral mimetic immunogen, polyinosinic-polycytidylic acid (poly(I:C)), is used to induce maternal immune activation in animal models of psychiatric disorders. In the mouse poly(I:C) model, the existence of segment filamentous bacteria (SFB) in the maternal intestine has been reported to be important for the induction of ASD-related behavioral alterations as well as atypical cortical development called cortical patches. This study aimed to elucidate the effect of a single poly(I:C) injection during embryonic day (E) 9 to E16 on offspring's behavior in the ensured absence of maternal SFB by vancomycin drinking in C57BL/6N mice. The cortical patches were not found at either injection timings with poly(I:C) or PBS vehicle, tested in male or female offspring at postnatal day 0 or 1. Prepulse inhibition was decreased in male adult offspring most strongly at poly(I:C) injection timings later than E11, whereas a modest but significant decrease was observed in female offspring with an injection during E12 to E15. The decrease in social interaction was observed in female offspring most conspicuously at injection timings later than E11, whereas a significant decrease was observed in male offspring with an injection during E12 to E15. In conclusion, this study indicated that behavioral alterations could be induced without maternal SFB. The effect on behavior was substantially different between males and females., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)
Published: 2023
Full Text: View/download PDF

32. Downregulation of 15-PGDH enhances MASH-HCC development via fatty acid-induced T-cell exhaustion.

Author: Hu X, Yasuda T, Yasuda-Yosihara N, Yonemura A, Umemoto T, Nakachi Y, Yamashita K, Semba T, Arima K, Uchihara T, Nishimura A, Bu L, Fu L, Wei F, Zhang J, Tong Y, Wang H, Iwamoto K, Fukuda T, Nakagawa H, Taniguchi K, Miyamoto Y, Baba H, and Ishimoto T
Abstract: Background & Aims: Hepatocellular carcinoma (HCC) mainly develops from chronic hepatitis. Metabolic dysfunction-associated steatohepatitis (MASH) has gradually become the main pathogenic factor for HCC given the rising incidence of obesity and metabolic diseases. 15-Hydroxyprostaglandin dehydrogenase (15-PGDH) degrades prostaglandin 2 (PGE2), which is known to exacerbate inflammatory responses. However, the role of PGE2 accumulation caused by 15 -PGDH downregulation in the development of MASH-HCC has not been determined., Methods: We utilised the steric animal model to establish a MASH-HCC model using wild-type and 15- Pgdh +/- mice to assess the significance of PGE2 accumulation in the development of MASH-HCC. Additionally, we analysed clinical samples obtained from patients with MASH-HCC., Results: PGE2 accumulation in the tumour microenvironment induced the production of reactive oxygen species in macrophages and the expression of cell growth-related genes and antiapoptotic genes. Conversely, the downregulation of fatty acid metabolism in the background liver promoted lipid accumulation in the tumour microenvironment, causing a decrease in mitochondrial membrane potential and CD8+ T-cell exhaustion, which led to enhanced development of MASH-HCC., Conclusions: 15- PGDH downregulation inactivates immune surveillance by promoting the proliferation of exhausted effector T cells, which enhances hepatocyte survival and proliferation and leads to the development of MASH-HCC., Impact and Implications: The suppression of PGE2-related inflammation and subsequent lipid accumulation leads to a reduction in the severity of MASH and inhibition of subsequent progression toward MASH-HCC., (© 2023 The Author(s).)
Published: 2023
Full Text: View/download PDF

33. Identification of novel oncogenes in oral cancer among elderly nonsmokers.

Author: Inoue H, Hirasaki M, Kogashiwa Y, Nakachi Y, Kuba K, Ebihara Y, Nakahira M, Yasuda M, Okuda A, and Sugasawa M
Subjects: Humans, Aged, Non-Smokers, Polymorphism, Single Nucleotide, Oncogenes genetics, Exome, Mouth Neoplasms genetics
Abstract: Objectives: In recent years, an increase in oral cancer among elderly nonsmokers has been noted. The aim of this study was to identify novel oncogenes in oral cancer in older nonsmokers., Material and Methods: Whole-exome sequencing (WES) data from 324 oral cancer patients were obtained from The Cancer Genome Atlas. Single nucleotide variants (SNVs) and insertions/deletions (INDELs) were extracted from the WES data of older patients. Fisher's exact test was performed to determine the specificity of variants in these genes. Finally, SNVs and INDELs were identified by target enrichment sequencing., Results: Gene ontology analysis of 112 genes with significant SNVs or INDELs in nonsmokers revealed that nonsynonymous SNVs in HECTD4 were significantly more frequent in nonsmokers than in smokers by target enrichment sequencing (p = .02)., Conclusions: Further investigation of the function of HECTD4 variants as oncogenes in older nonsmokers is warranted., (© 2023 The Authors. Clinical and Experimental Dental Research published by John Wiley & Sons Ltd.)
Published: 2023
Full Text: View/download PDF

34. Novel Bruton's tyrosine kinase inhibitor TAS5315 suppresses the progression of inflammation and joint destruction in rodent collagen-induced arthritis.

Author: Akasaka D, Iguchi S, Kaneko R, Yoshiga Y, Kajiwara D, Nakachi Y, Noma N, Tanaka K, Shimizu A, and Hosoi F
Subjects: Mice, Animals, Agammaglobulinaemia Tyrosine Kinase, Tyrosine Kinase Inhibitors, Rodentia, Inflammation drug therapy, Protein Kinase Inhibitors pharmacology, Protein Kinase Inhibitors therapeutic use, Arthritis, Experimental pathology, Arthritis, Rheumatoid
Abstract: Rheumatoid arthritis is an inflammatory autoimmune disease, characterized by autoantibody production, synovial inflammation, and joint destruction. Its pathogenesis is due to environmental factors and genetic backgrounds. Bruton's tyrosine kinase is a cytoplasmic non-receptor tyrosine kinase, expressed in most hematopoietic cell lineages, except T cells and plasma cells, and regulates various immune-related signaling pathways, thereby playing a crucial role in pathogenesis. Thus, inhibiting Bruton's tyrosine kinase may prove beneficial in treating autoimmune diseases. In the present study, we characterized Bruton's tyrosine kinase inhibitor, TAS5315, in vitro and evaluated its therapeutic effects in experimental arthritis models. TAS5315 markedly inhibited Bruton's tyrosine kinase enzyme activity and suppressed the B-cell receptor signaling pathway in Ramos cells. Moreover, it suppressed the expression of CD69, CD86, and MHC class II in mouse B lymphocytes and the production of TNF-α and MIP-1α in mouse macrophages and decreased bone resorption activity in mouse osteoclasts. Furthermore, it ameliorated the pathological changes in two rodent models of collagen-induced arthritis in vivo. TAS5315 improved bone mineral density and bone intensity. Thus, these results suggest that TAS5315 could be a promising therapeutic option for the treatment of rheumatoid arthritis., Competing Interests: All authors are employees at Taiho Pharmaceutical Co., Ltd. at time of studies. This does not alter adherence to PLOS ONE policies on sharing data and materials. None of the authors have competing interest relating to employment, consultancy, patents, products in development, marketed product or else., (Copyright: © 2023 Akasaka et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Published: 2023
Full Text: View/download PDF

35. Antipsychotics function as epigenetic age regulators in human neuroblastoma cells.

Author: Du J, Nakachi Y, Fujii A, Fujii S, Bundo M, and Iwamoto K
Published: 2022
Full Text: View/download PDF

36. Factors related to daily step counts of stroke patients during hospitalization in a convalescent rehabilitation ward.

Author: Yamada R, Shimizu S, Suzuki Y, Nakachi Y, Takemura N, Taira K, Yamazato T, Shimabukuro M, Tsunoda S, Shimose R, Ogura M, Higa J, Nakanishi T, and Matsunaga A
Subjects: Activities of Daily Living, Female, Hospitalization, Hospitals, Humans, Male, Recovery of Function, Treatment Outcome, Persons with Disabilities, Motor Disorders, Stroke diagnosis, Stroke therapy, Stroke Rehabilitation
Abstract: Objectives: Clarifying the factors related to decreased physical activity in post-stroke patients is essential for effective disease management. This study aimed to examine the factors influencing the amount of daily steps taken by post-stroke patients in a convalescent rehabilitation ward during activities other than rehabilitation (non-rehabilitation steps)., Materials and Methods: Eighty-nine post-stroke patients (60.8±14.4 years; 55 men) were enrolled. The inclusion criteria were walking independently within the ward and having a walking speed of ≥24 m/min. Data on patient clinical characteristics including age, sex, body mass index, stroke type, hemiparetic side, and time from stroke onset were collected. Stroke impairment and motor and cognitive functional disabilities were assessed using the Stroke Impairment Assessment Set and the Functional Independence Measure, respectively. The non-rehabilitation steps were calculated by subtracting the steps during the rehabilitation activities from the total steps using Fitbit Flex2., Results: The average number of non-rehabilitation steps was 4,523±2,339 steps/day. The hierarchical multiple regression analysis revealed that sex, motor disability, and the interaction term of stroke impairment with cognitive disability were significantly related to non-rehabilitation steps. Simple slope analysis demonstrated that the stroke impairment slope was steeper at lower levels than at higher levels of cognitive disability for non-rehabilitation steps., Conclusions: In addition to independent effects of sex and motor disability, this study found that stroke impairment and cognitive disability were interactively related to non-rehabilitation steps in post-stroke patients in a convalescent rehabilitation ward. These findings may provide useful information for managing physical activity in post-stroke patients after hospital discharge., Competing Interests: Declarations of interest None., (Copyright © 2022 Elsevier Inc. All rights reserved.)
Published: 2022
Full Text: View/download PDF

37. Cell-type-specific DNA methylation analysis of the frontal cortices of mutant Polg1 transgenic mice with neuronal accumulation of deleted mitochondrial DNA.

Author: Sugawara H, Bundo M, Kasahara T, Nakachi Y, Ueda J, Kubota-Sakashita M, Iwamoto K, and Kato T
Subjects: Animals, Epigenesis, Genetic, Frontal Lobe, Humans, Mice, Mice, Transgenic, Neurons, DNA Methylation genetics, DNA, Mitochondrial
Abstract: Bipolar disorder (BD) is a severe psychiatric disorder characterized by repeated conflicting manic and depressive states. In addition to genetic factors, complex gene-environment interactions, which alter the epigenetic status in the brain, contribute to the etiology and pathophysiology of BD. Here, we performed a promoter-wide DNA methylation analysis of neurons and nonneurons derived from the frontal cortices of mutant Polg1 transgenic (n = 6) and wild-type mice (n = 6). The mutant mice expressed a proofreading-deficient mitochondrial DNA (mtDNA) polymerase under the neuron-specific CamK2a promoter and showed BD-like behavioral abnormalities, such as activity changes and altered circadian rhythms. We identified a total of 469 differentially methylated regions (DMRs), consisting of 267 neuronal and 202 nonneuronal DMRs. Gene ontology analysis of DMR-associated genes showed that cell cycle-, cell division-, and inhibition of peptide activity-related genes were enriched in neurons, whereas synapse- and GABA-related genes were enriched in nonneurons. Among the DMR-associated genes, Trim2 and Lrpprc showed an inverse relationship between DNA methylation and gene expression status. In addition, we observed that mutant Polg1 transgenic mice shared several features of DNA methylation changes in postmortem brains of patients with BD, such as dominant hypomethylation changes in neurons, which include hypomethylation of the molecular motor gene and altered DNA methylation of synapse-related genes in nonneurons. Taken together, the DMRs identified in this study will contribute to understanding the pathophysiology of BD from an epigenetic perspective., (© 2022. The Author(s).)
Published: 2022
Full Text: View/download PDF

38. Comprehensive DNA Methylation Analysis of Human Neuroblastoma Cells Treated With Haloperidol and Risperidone.

Author: Du J, Nakachi Y, Kiyono T, Fujii S, Kasai K, Bundo M, and Iwamoto K
Abstract: Accumulating evidence suggests that the epigenetic alterations induced by antipsychotics contribute to the therapeutic efficacy. However, global and site-specific epigenetic changes by antipsychotics and those shared by different classes of antipsychotics remain poorly understood. We conducted a comprehensive DNA methylation analysis of human neuroblastoma cells cultured with antipsychotics. The cells were cultured with low and high concentrations of haloperidol or risperidone for 8 days. DNA methylation assay was performed with the Illumina HumanMethylation450 BeadChip. We found that both haloperidol and risperidone tended to cause hypermethylation changes and showed similar DNA methylation changes closely related to neuronal functions. A total of 294 differentially methylated probes (DMPs), including 197 hypermethylated and 97 hypomethylated DMPs, were identified with both haloperidol and risperidone treatment. Gene ontology analysis of the hypermethylated probe-associated genes showed enrichment of genes related to the regulation of neurotransmitter receptor activity and lipoprotein lipase activity. Pathway analysis identified that among the DMP-associated genes, SHANK1 and SHANK2 were the major genes in the neuropsychiatric disorder-related pathways. Our data would be valuable for understanding the mechanisms of action of antipsychotics from an epigenetic viewpoint., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Du, Nakachi, Kiyono, Fujii, Kasai, Bundo and Iwamoto.)
Published: 2021
Full Text: View/download PDF

39. Highly susceptible SARS-CoV-2 model in CAG promoter-driven hACE2-transgenic mice.

Author: Asaka MN, Utsumi D, Kamada H, Nagata S, Nakachi Y, Yamaguchi T, Kawaoka Y, Kuba K, and Yasutomi Y
Subjects: Animals, COVID-19 pathology, Disease Models, Animal, Disease Susceptibility, Female, Male, Mice, Inbred C57BL, Mice, Transgenic, Promoter Regions, Genetic, SARS-CoV-2 isolation & purification, Mice, Angiotensin-Converting Enzyme 2 genetics, COVID-19 genetics
Abstract: COVID-19, caused by SARS-CoV-2, has spread worldwide with dire consequences. To urgently investigate the pathogenicity of COVID-19 and develop vaccines and therapeutics, animal models that are highly susceptible to SARS-CoV-2 infection are needed. In the present study, we established an animal model highly susceptible to SARS-CoV-2 via the intratracheal tract infection in CAG promoter-driven human angiotensin-converting enzyme 2-transgenic (CAG-hACE2) mice. The CAG-hACE2 mice showed several severe symptoms of SARS-CoV-2 infection, with definitive weight loss and subsequent death. Acute lung injury with elevated cytokine and chemokine levels was observed at an early stage of infection in CAG-hACE2 mice infected with SARS-CoV-2. Analysis of the hACE2 gene in CAG-hACE2 mice revealed that more than 15 copies of hACE2 genes were integrated in tandem into the mouse genome, supporting the high susceptibility to SARS-CoV-2. In the developed model, immunization with viral antigen or injection of plasma from immunized mice prevented body weight loss and lethality due to infection with SARS-CoV-2. These results indicate that a highly susceptible model of SARS-CoV-2 infection in CAG-hACE2 mice via the intratracheal tract is suitable for evaluating vaccines and therapeutic medicines.
Published: 2021
Full Text: View/download PDF

40. Cell type-specific DNA methylation analysis of the prefrontal cortex of patients with schizophrenia.

Author: Ueda J, Bundo M, Nakachi Y, Kasai K, Kato T, and Iwamoto K
Subjects: DNA Methylation, Epigenesis, Genetic, Humans, Prefrontal Cortex, Schizophrenia genetics
Published: 2021
Full Text: View/download PDF

41. Decreased DNA methylation at promoters and gene-specific neuronal hypermethylation in the prefrontal cortex of patients with bipolar disorder.

Author: Bundo M, Ueda J, Nakachi Y, Kasai K, Kato T, and Iwamoto K
Subjects: Epigenesis, Genetic, Genome-Wide Association Study, Humans, Neurons, Prefrontal Cortex, Bipolar Disorder genetics, DNA Methylation genetics
Abstract: Bipolar disorder (BD) is a severe mental disorder characterized by repeated mood swings. Although genetic factors are collectively associated with the etiology of BD, the underlying molecular mechanisms, particularly how environmental factors affect the brain, remain largely unknown. We performed promoter-wide DNA methylation analysis of neuronal and nonneuronal nuclei in the prefrontal cortex of patients with BD (N = 34) and controls (N = 35). We found decreased DNA methylation at promoters in both cell types in the BD patients. Gene Ontology (GO) analysis of differentially methylated region (DMR)-associated genes revealed enrichment of molecular motor-related genes in neurons, chemokines in both cell types, and ion channel- and transporter-related genes in nonneurons. Detailed GO analysis further revealed that growth cone- and dendrite-related genes, including NTRK2 and GRIN1, were hypermethylated in neurons of BD patients. To assess the effect of medication, neuroblastoma cells were cultured under therapeutic concentrations of three mood stabilizers. We observed that up to 37.9% of DMRs detected in BD overlapped with mood stabilizer-induced DMRs. Interestingly, mood stabilizer-induced DMRs showed the opposite direction of changes in DMRs, suggesting the therapeutic effects of mood stabilizers. Among the DMRs, 12 overlapped with loci identified in a genome-wide association study (GWAS) of BD. We also found significant enrichment of neuronal DMRs in the loci reported in another GWAS of BD. Finally, we performed qPCR of DNA methylation-related genes and found that DNMT3B was overexpressed in BD. The cell-type-specific DMRs identified in this study will be useful for understanding the pathophysiology of BD., (© 2021. The Author(s).)
Published: 2021
Full Text: View/download PDF

42. Colonization of distant organs by tumor cells generating circulating homotypic clusters adaptive to fluid shear stress.

Author: Maeshiro M, Shinriki S, Liu R, Nakachi Y, Komohara Y, Fujiwara Y, Ohtsubo K, Yoshida R, Iwamoto K, Nakayama H, and Matsui H
Subjects: Animals, Cell Line, Humans, Mice, Head and Neck Neoplasms pathology, Neoplasm Metastasis pathology, Neoplastic Cells, Circulating pathology, Squamous Cell Carcinoma of Head and Neck pathology
Abstract: Once disseminated tumor cells (DTCs) arrive at a metastatic organ, they remain there, latent, and become seeds of metastasis. However, the clonal composition of DTCs in a latent state remains unclear. Here, we applied high-resolution DNA barcode tracking to a mouse model that recapitulated the metastatic dormancy of head and neck squamous cell carcinoma (HNSCC). We found that clones abundantly circulated peripheral blood dominated DTCs. Through analyses of multiple barcoded clonal lines, we identified specific subclonal population that preferentially generated homotypic circulating tumor cell (CTC) clusters and dominated DTCs. Despite no notable features under static conditions, this population significantly generated stable cell aggregates that were resistant to anoikis under fluid shear stress (FSS) conditions in an E-cadherin-dependent manner. Our data from various cancer cell lines indicated that the ability of aggregate-constituting cells to regulate cortical actin-myosin dynamics governed the aggregates' stability in FSS. The CTC cluster-originating cells were characterized by the expression of a subset of E-cadherin binding factors enriched with actin cytoskeleton regulators. Furthermore, this expression signature was associated with locoregional and metastatic recurrence in HNSCC patients. These results reveal a biological selection of tumor cells capable of generating FSS-adaptive CTC clusters, which leads to distant colonization.
Published: 2021
Full Text: View/download PDF

43. Identification and functional characterization of the extremely long allele of the serotonin transporter-linked polymorphic region.

Author: Ikegame T, Hidaka Y, Nakachi Y, Murata Y, Watanabe R, Sugawara H, Asai T, Kiyota E, Saito T, Ikeda M, Sasaki T, Hashimoto M, Ishikawa T, Takebayashi M, Iwata N, Kakiuchi C, Kato T, Kasai K, Bundo M, and Iwamoto K
Subjects: Aged, Alleles, Case-Control Studies, Cohort Studies, Genotype, Humans, Serotonin Plasma Membrane Transport Proteins genetics
Abstract: SLC6A4, which encodes the serotonin transporter, has a functional polymorphism called the serotonin transporter-linked polymorphic region (5-HTTLPR). The 5-HTTLPR consists of short (S) and long (L) alleles, each of which has 14 or 16 tandem repeats. In addition, the extralong (XL) and other rare alleles have been reported in 5-HTTLPR. Although they are more frequent in Asian and African than in other populations, the extent of variations and allele frequencies (AFs) were not addressed in a large population. Here, we report the AFs of the rare alleles in a large number of Japanese subjects (N = 2894) consisting of two cohorts. The first cohort (case-control study set, CCSS) consisted of 1366 subjects, including 485 controls and 881 patients with psychosis (bipolar disorder or schizophrenia). The second cohort (the Arao cohort study set, ACSS) consisted of 1528 elderly subjects. During genotyping, we identified 11 novel 5-HTTLPR alleles, including 3 XL alleles. One novel allele had the longest subunit ever reported, consisting of 28 tandem repeats. We named this XL 28-A. An in vitro luciferase assay revealed that XL 28-A has no transcriptional activity. XL 28-A was found in two unrelated patients with bipolar disorder in the CCSS and one healthy subject in the ACSS who did not show depressive symptoms or a decline in cognitive function. Therefore, it is unlikely that XL 28-A is associated with psychiatric disorders, despite its apparent functional deficit. Our results suggest that unraveling the complex genetic variations of 5-HTTLPR will be important for further understanding its role in psychiatric disorders.
Published: 2021
Full Text: View/download PDF

44. Use of the Illumina EPIC methylation array for epigenomic research in the crab-eating macaque (Macaca fascicularis).

Author: Nakachi Y, Ishii K, Bundo M, Masuda T, and Iwamoto K
Subjects: Animals, Female, Macaca fascicularis, Male, Biomedical Research methods, Computational Biology methods, DNA Methylation physiology, Epigenesis, Genetic physiology, Epigenomics methods
Abstract: Background: Commercially available Illumina DNA methylation arrays (HumanMethylation 27K, HumanMethylation450, and MethylationEPIC BeadChip) can be used for comprehensive DNA methylation analyses of not only the human genome but also other mammalian genomes, ranging from those of nonhuman primates to those of rodents. However, practical application of the EPIC array to the crab-eating macaque has not been reported., Methods: Through bioinformatic analyses involving cross-species comparison and consideration of probe performance, we selected array probes that can be reliably used for the crab-eating macaque genome. A DNA methylation assay using an EPIC array was performed on genomic DNA extracted from the brains of five crab-eating macaques. The obtained DNA methylation data were compared with a publicly available dataset., Results: Among the 865 918 probes in the EPIC array, a total of 183 509 probes (21.2%) were selected as high-confidence array probes in the crab-eating macaque. Subsequent comparisons revealed that the data from these probes showed good concordance with other DNA methylation datasets of the crab-eating macaque., Conclusion: The selected high-confidence array probes would be useful for high-throughput DNA methylation assays of the crab-eating macaque., (© 2020 The Authors. Neuropsychopharmacology Reports published by John Wiley & Sons Australia, Ltd on behalf of The Japanese Society of Neuropsycho Pharmacology.)
Published: 2020
Full Text: View/download PDF

45. Establishment of Quantitative PCR Assays for Active Long Interspersed Nuclear Element-1 Subfamilies in Mice and Applications to the Analysis of Aging-Associated Retrotransposition.

Author: Kuroki R, Murata Y, Fuke S, Nakachi Y, Nakashima J, Kujoth GC, Prolla TA, Bundo M, Kato T, and Iwamoto K
Abstract: The retrotransposon long interspersed nuclear element-1 (LINE-1) can autonomously increase its copy number within a host genome through the retrotransposition process. LINE-1 is active in the germline and in neural progenitor cells, and its somatic retrotransposition activity has a broad impact on neural development and susceptibility to neuropsychiatric disorders. The method to quantify the genomic copy number of LINE-1 would be important in unraveling the role of retrotransposition, especially in the brain. However, because of the species-specific evolution of LINE-1 sequences, methods for quantifying the copy number should be independently developed. Here, we developed a quantitative PCR (qPCR) assay to measure the copy number of active LINE-1 subfamilies in mice. Using the assay, we investigated aging-associated alterations of LINE-1 copy number in several brain regions in wild-type mice and Polg +/D257A mice as a model for accelerated aging. We found that aged Polg +/D257A mice showed higher levels of the type GfII LINE-1 in the basal ganglia than the wild-type mice did, highlighting the importance of assays that focus on an individual active LINE-1 subfamily., (Copyright © 2020 Kuroki, Murata, Fuke, Nakachi, Nakashima, Kujoth, Prolla, Bundo, Kato and Iwamoto.)
Published: 2020
Full Text: View/download PDF

46. Correction: Fam57b (family with sequence similarity 57, member B), a novel peroxisome proliferator-activated receptor γ target gene that regulates adipogenesis through ceramide synthesis.

Author: Yamashita-Sugahara Y, Tokuzawa Y, Nakachi Y, Kanesaki-Yatsuka Y, Matsumoto M, Mizuno Y, and Okazaki Y
Published: 2020
Full Text: View/download PDF

47. Hypermethylation of Corticotropin Releasing Hormone Receptor-2 Gene in Ulcerative Colitis Associated Colorectal Cancer.

Author: Kobayashi M, Matsubara N, Nakachi Y, Okazaki Y, Uchino M, Ikeuchi H, Song J, Kimura K, Yasuhara M, Babaya A, Yamano T, Ikeda M, Nishikawa H, Matsuda I, Hirota S, and Tomita N
Subjects: Adult, Colon pathology, CpG Islands genetics, Female, Humans, Intestinal Mucosa pathology, Male, Middle Aged, Colitis, Ulcerative genetics, Colorectal Neoplasms genetics, DNA Methylation genetics, Receptors, Corticotropin-Releasing Hormone genetics
Abstract: Background/aim: The difficulty of early diagnosis of colitis associated colorectal cancer (CACRC) due to colonic mucosal changes in long-standing ulcerative colitis (UC) patients is often experienced in daily clinical practice. Noninvasive objective monitoring for cancer development is advantageous for optimizing treatment strategies in UC patients. We aimed to examine the epigenetic alterations occurring in CACRC, focusing on DNA hypermethylation of CpG islands., Materials and Methods: The level of DNA methylation in CpG cites was compared between CACRC and the counterpart non-tumorous mucosa using Infinium HumanMethylation 450K BeadChip., Results: Our subjects included 3 males and 3 females (median age, 49.5 years). The 450K CpG site DNA methylation microarray revealed that the difference in β value (level of hypermethylation) was the highest for corcicotropin releasing hormone receptor 2 (CRHR2) between CACRC and counterpart non-tumorous mucosa., Conclusion: Detection of hypermethylation of CRHR2 may be promising for cancer screening in UC patients., (Copyright© 2020, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)
Published: 2020
Full Text: View/download PDF

48. Evaluation of the usefulness of saliva for DNA methylation analysis in cohort studies.

Author: Murata Y, Fujii A, Kanata S, Fujikawa S, Ikegame T, Nakachi Y, Zhao Z, Jinde S, Kasai K, Bundo M, and Iwamoto K
Subjects: Adult, Epigenesis, Genetic, Female, Humans, Male, Young Adult, CpG Islands, DNA Methylation, Saliva
Abstract: Introduction: Epigenetic information such as DNA methylation is a useful biomarker that reflects complex gene-environmental interaction. Peripheral tissues such as blood and saliva are commonly collected as the source of genomic DNA in cohort studies. Epigenetic studies mainly use blood, while a few studies have addressed the epigenetic characteristics of saliva., Methods: The effects of methods for DNA extraction and purification from saliva on DNA methylation were surveyed using Illumina Infinium HumanMethylation450 BeadChip. Using 386 661 probes, DNA methylation differences between blood and saliva from 22 healthy volunteers, and their functional and structural characteristics were examined. CpG sites with DNA methylation levels showing large interindividual variations in blood were evaluated using saliva DNA methylation profiles., Results: Genomic DNA prepared by simplified protocol from saliva showed a similar quality DNA methylation profile to that derived from the manufacturer provided protocol. Consistent with previous studies, the DNA methylation profiles of blood and saliva showed high correlations. Blood showed 1,514 hypomethylated and 2099 hypermethylated probes, suggesting source-dependent DNA methylation patterns. CpG sites with large methylation difference between the two sources were underrepresented in the promoter regions and enriched within gene bodies. CpG sites with large interindividual methylation variations in blood also showed considerable variations in saliva., Conclusion: In addition to high correlation in DNA methylation profiles, CpG sites showing large interindividual DNA methylation differences were similar between blood and saliva, ensuring saliva could be a suitable alternative source for genomic DNA in cohort studies. Consideration of source-dependent DNA methylation differences will, however, be necessary., (© 2019 The Authors. Neuropsychopharmacology Reports published by John Wiley & Sons Australia, Ltd on behalf of the Japanese Society of NeuropsychoPharmacology.)
Published: 2019
Full Text: View/download PDF

49. Expressions of 10 genes as candidate predictors of recurrence in stage III colon cancer patients receiving adjuvant oxaliplatin-based chemotherapy.

Author: Kumamoto K, Nakachi Y, Mizuno Y, Yokoyama M, Ishibashi K, Kosugi C, Koda K, Kobayashi M, Tanakaya K, Matsunami T, Eguchi H, Okazaki Y, and Ishida H
Abstract: Approximately 30% patients with stage III colon cancer (CC) develop local recurrence and/or distant metastasis, even if postoperative adjuvant chemotherapy with oxaliplatin plus 5-fluorouracil and leucovorin (5-FU/LV) has been completed. In the present study, molecular analysis was performed to identify molecular markers of tumor recurrence in patients with stage III CC receiving oxaliplatin-based adjuvant chemotherapy. The FACOS study was conducted as a phase II study to evaluate the safety and efficacy of oxaliplatin-based treatment for stage III CC patients. Of the 132 CC patients enrolled in the present study, gene expression analysis using a microarray was conducted in 51 patients. Of these 51 patients, 6 developed recurrence within 5 years. The topmost 5% genes that showed differential expressions between cases that developed/did not develop recurrence were selected, and a set of predictive molecular markers for recurrence was identified. Of the 34,694 genes in the microarray, 1,734 genes were extracted as topmost 5% genes showing differential expressions between cases with and without recurrence. Among these, 10 genes, including ADH1A, ADH1C, CA12, CHP2, HMGCS2, SNAR-A1, TPI1, MS4A12, PLA2G10 and PTPRO , were identified as markers that could clearly divide patients with and without recurrence. Although several prediction models of tumor recurrence have been reported for CC, the set of 10 genes that the present study identified may be useful to predict the risk of recurrence in stage III CC patients receiving oxaliplatin-based adjuvant chemotherapy. Based on these results, high-risk patients with CC should be carefully observed to detect tumor recurrence during the follow-up period.
Published: 2019
Full Text: View/download PDF

50. Murine osteoclasts secrete serine protease HtrA1 capable of degrading osteoprotegerin in the bone microenvironment.

Author: Ochiai N, Nakachi Y, Yokoo T, Ichihara T, Eriksson T, Yonemoto Y, Kato T, Ogata H, Fujimoto N, Kobayashi Y, Udagawa N, Kaku S, Ueki T, Okazaki Y, Takahashi N, and Suda T
Subjects: Animals, Bone Marrow Cells metabolism, Cell Differentiation, Cells, Cultured, High-Temperature Requirement A Serine Peptidase 1 genetics, Macrophages metabolism, Matrix Metalloproteinase 9 metabolism, Mice, Osteoblasts metabolism, Osteogenesis genetics, Osteoprotegerin genetics, Proteolysis, Sequence Analysis, RNA, Bone and Bones metabolism, Cellular Microenvironment genetics, High-Temperature Requirement A Serine Peptidase 1 metabolism, Osteoclasts metabolism, Osteoprotegerin metabolism
Abstract: Osteoclasts are multinucleated cells responsible for bone resorption. The differentiation of osteoclasts from bone marrow macrophages (BMMs) is induced by receptor activator of NF-κB ligand (RANKL). Osteoprotegerin (OPG), a decoy receptor of RANKL, inhibits osteoclastogenesis by blocking RANKL signaling. Here we investigated the degradation of OPG in vitro. Osteoclasts, but not BMMs, secreted OPG-degrading enzymes. Using mass spectrometry and RNA-sequencing analysis, we identified high-temperature requirement A serine peptidase 1 (HtrA1) as an OPG-degrading enzyme. HtrA1 did not degrade OPG pre-reduced by dithiothreitol, suggesting that HtrA1 recognizes the three-dimensional structure of OPG. HtrA1 initially cleaved the amide bond between leucine 90 and glutamine 91 of OPG, then degraded OPG into small fragments. Inhibitory activity of OPG on RANKL-induced osteoclastogenesis was suppressed by adding HtrA1 in RAW 264.7 cell cultures. These results suggest that osteoclasts potentially prepare a microenvironment suitable for osteoclastogenesis. HtrA1 may be a novel drug target for osteoporosis., Competing Interests: The authors declare no competing interests.
Published: 2019
Full Text: View/download PDF

Catalog

Books, media, physical & digital resources

See catalog results

Searchworks

Select search scope, currently: Articles Catalog books, media & more in Jio Institute collections Articles journal articles & other e-resources

Search

Search Constraints

Refine your results

Search Limiters

Topic

Publication Year Range

Language

Publication Type

Journal

Database

Publisher

85 results on '"Nakachi, Y."'

Search Results

Catalog

Select search scope, currently: Articles

Catalog

books, media & more in Jio Institute collections

Articles

journal articles & other e-resources