Author: "Kasukawa T" - Searchworks@Jio Institute Digital Library Search Results

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153 results on '"Kasukawa T"'

1. The Transcriptional Landscape of the Mammalian Genome

Author: Carninci, P., Kasukawa, T., Katayama, S., Gough, J., Frith, M. C., Maeda, N., Oyama, R., Ravasi, T., Lenhard, B., Wells, C., Kodzius, R., Shimokawa, K., Bajic, V. B., Brenner, S. E., Batalov, S., Forrest, A. R. R., Zavolan, M., Davis, M. J., Wilming, L. G., Aidinis, V., Allen, J. E., Ambesi-Impiombato, A., Apweiler, R., Aturaliya, R. N., Bailey, T. L., Bansal, M., Baxter, L., Beisel, K. W., Bersano, T., Bono, H., Chalk, A. M., Chiu, K. P., Choudhary, V., Christoffels, A., Clutterbuck, D. R., Crowe, M. L., Dalla, E., Dalrymple, B. P., de Bono, B., Della Gatta, G., di Bernardo, D., Down, T., Engstrom, P., Fagiolini, M., Faulkner, G., Fletcher, C. F., Fukushima, T., Furuno, M., Futaki, S., Gariboldi, M., Georgii-Hemming, P., Gingeras, T. R., Gojobori, T., Green, R. E., Gustincich, S., Harbers, M., Hayashi, Y., Hensch, T. K., Hirokawa, N., Hill, D., Huminiecki, L., Iacono, M., Ikeo, K., Iwama, A., Ishikawa, T., Jakt, M., Kanapin, A., Katoh, M., Kawasawa, Y., Kelso, J., Kitamura, H., Kitano, H., Kollias, G., Krishnan, S. P. T., Kruger, A., Kummerfeld, S. K., Kurochkin, I. V., Lareau, L. F., Lazarevic, D., Lipovich, L., Liu, J., Liuni, S., McWilliam, S., Babu, M. Madan, Madera, M., Marchionni, L., Matsuda, H., Matsuzawa, S., Miki, H., Mignone, F., Miyake, S., Morris, K., Mottagui-Tabar, S., Mulder, N., Nakano, N., Nakauchi, H., Ng, P., Nilsson, R., Nishiguchi, S., Nishikawa, S., Nori, F., Ohara, O., Okazaki, Y., Orlando, V., Pang, K. C., Pavan, W. J., Pavesi, G., Pesole, G., Petrovsky, N., Piazza, S., Reed, J., Reid, J. F., Ring, B. Z., Ringwald, M., Rost, B., Ruan, Y., Salzberg, S. L., Sandelin, A., Schneider, C., Schöbach, C., Sekiguchi, K., Semple, C. A. M., Seno, S., Sessa, L., Sheng, Y., Shibata, Y., Shimada, H., Shimada, K., Silva, D., Sinclair, B., Sperling, S., Stupka, E., Sugiura, K., Sultana, R., Takenaka, Y., Taki, K., Tammoja, K., Tan, S. L., Tang, S., Taylor, M. S., Tegner, J., Teichmann, S. A., Ueda, H. R., van Nimwegen, E., Verardo, R., Wei, C. L., Yagi, K., Yamanishi, H., Zabarovsky, E., Zhu, S., Zimmer, A., Hide, W., Bult, C., Grimmond, S. M., Teasdale, R. D., Liu, E. T., Brusic, V., Quackenbush, J., Wahlestedt, C., Mattick, J. S., Hume, D. A., Kai, C., Sasaki, D., Tomaru, Y., Fukuda, S., Kanamori-Katayama, M., Suzuki, M., Aoki, J., Arakawa, T., Iida, J., Imamura, K., Itoh, M., Kato, T., Kawaji, H., Kawagashira, N., Kawashima, T., Kojima, M., Kondo, S., Konno, H., Nakano, K., Ninomiya, N., Nishio, T., Okada, M., Plessy, C., Shibata, K., Shiraki, T., Suzuki, S., Tagami, M., Waki, K., Watahiki, A., Okamura-Oho, Y., Suzuki, H., and Kawai, J.
Published: 2005

2. Antisense Transcription in the Mammalian Transcriptome

Author: Katayama, S., Tomaru, Y., Kasukawa, T., Waki, K., Nakanishi, M., Nakamura, M., Nishida, H., Yap, C. C., Suzuki, M., Kawai, J., Suzuki, H., Carninci, P., Hayashizaki, Y., Wells, C., Frith, M., Ravasi, T., Pang, K. C., Hallinan, J., Mattick, J., Hume, D. A., Lipovich, L., Batalov, S., Engström, P. G., Mizuno, Y., Faghihi, M. A., Sandelin, A., Chalk, A. M., Mottagui-Tabar, S., Liang, Z., Lenhard, B., and Wahlestedt, C.
Published: 2005

3. Author Correction: Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network.

Author: Grapotte, M, Saraswat, M, Bessière, C, Menichelli, C, Ramilowski, JA, 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, MC, FANTOM consortium, Chatelain, C, Carninci, P, de Hoon, MJL, Wasserman, WW, Bréhélin, L, Lecellier, C-H, Grapotte, M, Saraswat, M, Bessière, C, Menichelli, C, Ramilowski, JA, 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, MC, FANTOM consortium, Chatelain, C, Carninci, P, de Hoon, MJL, Wasserman, WW, Bréhélin, L, and Lecellier, C-H
Published: 2022

4. 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
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5. Functional annotation of human long noncoding RNAs via molecular phenotyping (vol 30, pg 1060, 2020)

Author: Ramilowski, JA, Yip, CW, Agrawal, S, Chang, J-C, Ciani, Y, Kulakovskiy, IV, Mendez, M, Ooi, JLC, Ouyang, JF, Parkinson, N, Petri, A, Roos, L, Severin, J, Yasuzawa, K, Abugessaisa, I, Akalin, A, Antonov, IV, Arner, E, Bonetti, A, Bono, H, Borsari, B, Brombacher, F, Cameron, CJF, Cannistraci, CV, Cardenas, R, Cardon, M, Chang, H, Dostie, J, Ducoli, L, Favorov, A, Fort, A, Garrido, D, Gil, N, Gimenez, J, Guler, R, Handoko, L, Harshbarger, J, Hasegawa, A, Hasegawa, Y, Hashimoto, K, Hayatsu, N, Heutink, P, Hirose, T, Imada, EL, Itoh, M, Kaczkowski, B, Kanhere, A, Kawabata, E, Kawaji, H, Kawashima, T, Kelly, ST, Kojima, M, Kondo, N, Koseki, H, Kouno, T, Kratz, A, Kurowska-Stolarska, M, Kwon, ATJ, Leek, J, Lennartsson, A, Lizio, M, Lopez-Redondo, F, Luginbuhl, J, Maeda, S, Makeev, VJ, Marchionni, L, Medvedeva, YA, Minoda, A, Muller, F, Munoz-Aguirre, M, Murata, M, Nishiyori, H, Nitta, KR, Noguchi, S, Noro, Y, Nurtdinov, R, Okazaki, Y, Orlando, V, Paquette, D, Parr, CJC, Rackham, OJL, Rizzu, P, Martinez, DFS, Sandelin, A, Sanjana, P, Semple, CAM, Shibayama, Y, Sivaraman, DM, Suzuki, T, Szumowski, SC, Tagami, M, Taylor, MS, Terao, C, Thodberg, M, Thongjuea, S, Tripathi, V, Ulitsky, I, Verardo, R, Vorontsov, IE, Yamamoto, C, Young, RS, Baillie, JK, Forrest, ARR, Guigo, R, Hoffman, MM, Hon, CC, Kasukawa, T, Kauppinen, S, Kere, J, Lenhard, B, Schneider, C, Suzuki, H, Yagi, K, De Hoon, MJL, Shin, JW, Carninci, P, and Wellcome Trust
Subjects: Genetics & Heredity, Biochemistry & Molecular Biology, Science & Technology, Biotechnology & Applied Microbiology, Bioinformatics, 06 Biological Sciences, Life Sciences & Biomedicine, 11 Medical and Health Sciences
Published: 2020

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

Author: Grapotte, M, Saraswat, M, Bessière, C, Menichelli, C, Ramilowski, JA, 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, MC, FANTOM consortium, Chatelain, C, Carninci, P, de Hoon, MJL, Wasserman, WW, Bréhélin, L, Lecellier, C-H, Grapotte, M, Saraswat, M, Bessière, C, Menichelli, C, Ramilowski, JA, 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, MC, FANTOM consortium, Chatelain, C, Carninci, P, de Hoon, MJL, Wasserman, WW, Bréhélin, L, and Lecellier, C-H
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.
Published: 2021

7. Analysis of the mouse transcriptome based on functional annotation of 60,770 full-length cDNAs

Author: Okazaki, Y., Furuno, M., Kasukawa, T., Adachi, J., Bono, H., Kondo, S., Nikaido, I., Osato, N., Saito, R., Suzuki, H., Yamanaka, I., Kiyosawa, H., Yagi, K., Tomaru, Y., Hasegawa, Y., Nogami, A., Schonbach, C., Gojobori, T., Baldarelli, R., Hill, D. P., Bult, C., Hume, D. A., Quackenbush, J., Schriml, L. M., Kanapin, A., Matsuda, H., Batalov, S., Beisel, K. W., Blake, J. A., Bradt, D., Brusic, V., Chothia, C., Corbani, L. E., Cousins, S., Dalla, E., Dragani, T. A., Fletcher, C. F., Forrest, A., Frazer, K. S., Gaasterland, T., Gariboldi, M., Gissi, C., Godzik, A., Gough, J., Grimmond, S., Gustincich, S., Hirokawa, N., Jackson, I. J., Jarvis, E. D., Kanai, A., Kawaji, H., Kawasawa, Y., Kedzierski, R. M., King, B. L., Konagaya, A., Kurochkin, I. V., Lee, Y., Lenhard, B., Lyons, P. A., Maglott, D. R., Maltais, L., Marchionni, L., McKenzie, L., Miki, H., Nagashima, T., Numata, K., Okido, T., Pavan, W. J., Pertea, G., Pesole, G., Petrovsky, N., Pillai, R., Pontius, J. U., Qi, D., Ramachandran, S., Ravasi, T., Reed, J. C., Reed, D. J., Reid, J., Ring, B. Z., Ringwald, M., Sandelin, A., Schneider, C., Semple, C. A. M., Setou, M., Shimada, K., Sultana, R., Takenaka, Y., Taylor, M. S., Teasdale, R. D., Tomita, M., Verardo, R., Wagner, L., Wahlestedt, C., Wang, Y., Watanabe, Y., Wells, C., Wilming, L. G., Wynshaw-Boris, A., Yanagisawa, M., Yang, I., Yang, L., Yuan, Z., Zavolan, M., Zhu, Y., Zimmer, A., Carninci, P., Hayatsu, N., Hirozane-Kishikawa, T., Konno, H., Nakamura, M., Sakazume, N., Sato, K., Shiraki, T., Waki, K., Kawai, J., Aizawa, K., Arakawa, T., Fukuda, S., Hara, A., Hashizume, W., Imotani, K., Ishii, Y., Itoh, M., Kagawa, I., Miyazaki, A., Sakai, K., Sasaki, D., Shibata, K., Shinagawa, A., Yasunishi, A., Yoshino, M., Waterston, R., Lander, E. S., Rogers, J., Birney, E., and Hayashizaki, Y.
Abstract: Author(s): The FANTOM Consortium and the RIKEN Genome Exploration Research Group Phase I & II Team*; FANTOM Consortium:; Y. Okazaki [1, 2]; M. Furuno [1]; T. Kasukawa [1, 3]; J. [...]
Published: 2002
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8. An integrated expression atlas of miRNAs and their promoters in human and mouse

Author: De Rie D., Abugessaisa I., Alam T., Arner E., Arner P., Ashoor H., Åström G., Babina M., Bertin N., Burroughs A., Carlisle A., Daub C., Detmar M., Deviatiiarov R., Fort A., Gebhard C., Goldowitz D., Guhl S., Ha T., Harshbarger J., Hasegawa A., Hashimoto K., Herlyn M., Heutink P., Hitchens K., Hon C., Huang E., Ishizu Y., Kai C., Kasukawa T., Klinken P., Lassmann T., Lecellier C., Lee W., Lizio M., Makeev V., Mathelier A., Medvedeva Y., Mejhert N., Mungall C., Noma S., Ohshima M., Okada-Hatakeyama M., Persson H., Rizzu P., Roudnicky F., Sætrom P., Sato H., Severin J., Shin J., Swoboda R., Tarui H., Toyoda H., Vitting-Seerup K., Winteringham L., Yamaguchi Y., Yasuzawa K., Yoneda M., Yumoto N., Zabierowski S., Zhang P., Wells C., Summers K., Kawaji H., Sandelin A., Rehli M., and Hayashizaki Y.
Abstract: © 2017 Nature America, Inc., part of Springer Nature. MicroRNAs (miRNAs) are short non-coding RNAs with key roles in cellular regulation. As part of the fifth edition of the Functional Annotation of Mammalian Genome (FANTOM5) project, we created an integrated expression atlas of miRNAs and their promoters by deep-sequencing 492 short RNA (sRNA) libraries, with matching Cap Analysis Gene Expression (CAGE) data, from 396 human and 47 mouse RNA samples. Promoters were identified for 1,357 human and 804 mouse miRNAs and showed strong sequence conservation between species. We also found that primary and mature miRNA expression levels were correlated, allowing us to use the primary miRNA measurements as a proxy for mature miRNA levels in a total of 1,829 human and 1,029 mouse CAGE libraries. We thus provide a broad atlas of miRNA expression and promoters in primary mammalian cells, establishing a foundation for detailed analysis of miRNA expression patterns and transcriptional control regions.
Published: 2017

9. Systematic analysis of transcription start sites in avian development

Author: Lizio M., Deviatiiarov R., Nagai H., Galan L., Arner E., Itoh M., Lassmann T., Kasukawa T., Hasegawa A., Ros M., Hayashizaki Y., Carninci P., Forrest A., Kawaji H., Gusev O., and Sheng G.
Abstract: © 2017 Lizio et al. Cap Analysis of Gene Expression (CAGE) in combination with single-molecule sequencing technology allows precision mapping of transcription start sites (TSSs) and genome-wide capture of promoter activities in differentiated and steady state cell populations. Much less is known about whether TSS profiling can characterize diverse and non-steady state cell populations, such as the approximately 400 transitory and heterogeneous cell types that arise during ontogeny of vertebrate animals. To gain such insight, we used the chick model and performed CAGE-based TSS analysis on embryonic samples covering the full 3-week developmental period. In total, 31,863 robust TSS peaks ( > 1 tag per million [TPM]) were mapped to the latest chicken genome assembly, of which 34% to 46% were active in any given developmental stage. ZENBU, a web-based, open-source platform, was used for interactive data exploration. TSSs of genes critical for lineage differentiation could be precisely mapped and their activities tracked throughout development, suggesting that non-steady state and heterogeneous cell populations are amenable to CAGE-based transcriptional analysis. Our study also uncovered a large set of extremely stable housekeeping TSSs and many novel stage-specific ones. We furthermore demonstrated that TSS mapping could expedite motif-based promoter analysis for regulatory modules associated with stage-specific and housekeeping genes. Finally, using Brachyury as an example, we provide evidence that precise TSS mapping in combination with Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)-on technology enables us, for the first time, to efficiently target endogenous avian genes for transcriptional activation. Taken together, our results represent the first report of genome-wide TSS mapping in birds and the first systematic developmental TSS analysis in any amniote species (birds and mammals). By facilitating promoter-based molecular analysis and genetic manipulation, our work also underscores the value of avian models in unravelling the complex regulatory mechanism of cell lineage specification during amniote development.
Published: 2017

10. 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

11. 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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12. 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
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13. General Lectures

Author: Yamaoka, Y., Nagai, T., Furuta, K., Inagawa, T., Sugiya, T., Kai, T., Amamoto, H., Okunara, T., Miyoshi, A., Araya, S., Sometani, T., Ogura, T., Yamato, T., Hirata, S., Hashimoto, T., Hamanaka, Y., Shakudo, Y., Ozaki, T., Noda, S., Kobayashi, K., Sasaki, K., Matsuura, R., Ueno, H., Ito, T., Umayahara, A., Koga, Y., Watanabe, K., Nabeya, K., Shimura, I., Ohyama, O., Komatsuzaki, T., Ogoshi, K., Hara, Y., Hiratsuka, H., Kubo, N., Masuda, H., Inoue, S., Arakawa, H., Koizumi, K., Mukozima, K., Inoue, Y., Hosaka, H., Kikuchi, N., Yoshida, H., Sakumoto, I., Inaba, M., Yokoi, Y., Abei, T., Iwama, S., Shirota, A., Miki, M., Ōkawa, K., Onda, M., Yoshioka, M., Shiba, T., Yamashita, K., Moriyama, Y., Adachi, K., Miyashita, M., Henmi, H., Egami, K., Toi, K., Fukiwake, T., Ito, H., Tamesue, N., Ohsato, K., Nagamitsu, S., Nishimura, M., Yamashita, Y., Yao, T., Mizuno, S., Tanabe, M., Yanase, M., Suzuki, K., Suzuki, K., Hayashi, K., Nishitani, T., Katake, K., Iwasa, N., Nishimura, S., Miyoshi, M., Fukumoto, K., Fujii, H., Inatomi, I., Nakajima, H., Hojo, Y., Tosaka, T., Kaneko, H., Yoshikawa, K., Mori, K., Uematsu, T., Takahashi, T., Morikawa, S., Hashi, M., Sakamoto, T., Kimura, A., Sasagawa, T., Maeda, Y., Matsukawa, M., Aizawa, T., Tabata, I., Munakata, A., Toda, S., Tajima, T., Matsunaga, F., Ogata, T., Nakayama, K., Nakayama, T., Minota, S., Otani, A., Takei, S., Tanaka, M., Miki, H., Hojo, K., Hirota, E., Sano, R., Murashima, Y., Okuuti, Y., Miwa, K., Suga, T., Yaosaka, T., Namiki, M., Kawauti, H., Nakagawa, K., Kasukawa, T., Kobayashi, S., Watanabe, H., Yamagata, S., Narasaka, T., Imai, H., Tsuneoka, T., Watanabe, H., Hoshi, K., Nishiyama, S., Hoshi, K., Fushimi, I., Hirai, T., Katsuda, M., Hirose, M., Yokomori, H., Matsumoto, T., Watanabe, N., Matsuura, K., Ishibashi, T., Nakata, S., Takei, C., Asano, H., Miyoshi, H., Hidaka, T., Dodo, H., Kitada, A., Nakamura, T., Sakata, S., Kitamura, S., Nakamua, T., Sakata, S., Kitamura, S., Agata, E., Aikawa, K., Oshima, A., Fujimoto, I., Kobayashi, T., Asakawa, Y., Kusakari, M., Abe, C., Tarumi, S., Yamashita, T., Takasu, S., Komase, Y., Hamada, H., Shoji, F., Saito, S., Takayama, T., Fujita, R., Kumura, F., Umeda, K., Okamoto, S., Nishio, H., Shintani, Y., Saitoh, K., Tatara, T., Iwamiya, K., Tamura, M., Tamura, K., Nakano, A., Tamura, U., Nakajima, T., Ichioka, G., Takeuchi, Y., Ayada, K., Torisu, R., Kamada, H., Matuoka, R., Turuoka, M., Sagara, Y., Nakamura, S., Sakasita, O., Mashimo, N., Sekiguchi, T., Kobayashi, S., Kishimoto, H., Takeuchi, T., Murakami, S., Koga, S., Ueno, M., Nishizawa, M., Nomoto, K., Kariya, A., Hayashi, M., Kobayashi, S., Mizuno, K., Mayama, S., Shinozuka, T., Maruyama, T., Ogiwara, T., Okui, K., Higurashi, K., Ito, T., Miyata, Y., Tamura, T., Ikeda, S., Nakata, J., Oshima, H., Mori, S., Otsuka, Y., Oki, I., Tasaka, S., Yamahatsu, J., Inaba, E., Sanada, K., Oura, T., Kinoshita, T., Akagi, M., Katsuhisa, F., Misumi, A., Urashima, K., Ninomiya, S., Hukami, M., Mori, T., Matsuo, Y., Seki, A., Kitamura, T., Mori, H., Yokota, R., Kawashima, S., Itoshima, T., Shimada, Y., Itoshima, T., Inoue, T., Fukuhara, J., Kubota, M., Ohta, W., Ohta, W., Kagaya, T., Abe, R., Kai, Y., Katono, S., Komatsu, K., Masuda, H., Inoue, S., Arakawa, H., Hamajima, T., Kitamura, T., Nakagawa, F., Tamura, H., Kiyonaga, G., Inui, H., Asai, H., Hayashi, N., Obata, H., Toki, F., Kakae, U., Yamauchi, D., Hisamitsu, T., Aziki, K., Tamiya, M., Watanabe, S., Kurokawa, K., Takemoto, T., Murakami, S., Kessoku, Y., Kuwana, H., Hino, K., Kato, A., Ito, A., Arakawa, Y., Ohono, Y., Hase, M., Ariga, K., Usui, R., Kutsukake, S., Nagamori, S., Nagano, H., Shimano, K., Ohya, T., Kikuchi, S., Ito, M., Hidano, S., Banno, H., Tomura, A., Kato, K., Koyama, T., Komatsu, T., Takei, T., Tomimura, K., Yamauchi, M., Sato, G., Sato, R., Haga, M., Toyokawa, S., Yamamoto, J., Ohtomi, S., Ishibashi, Y., Fukuda, M., Endo, R., Ueno, Y., Hisamitsu, T., Sasaki, T., Kobayashi, C., Kusakari, T., Yajima, T., Maeda, M., Kotoda, K., Okuda, K., Ariga, H., Takazawa, G., Nakamura, Y., Ohbayashi, A., Mitsui, H., Nakata, K., Suematsu, T., Kashiwagi, T., Hayashi, N., Baba, T., Tobimatsu, Y., Kamada, T., Abe, H., Matsuoka, K., Matsushima, S., Kamisaka, Y., Kitsuki, T., Ohnuki, H., Fujii, M., Inoue, R., Yamamoto, T., Wakisaka, G., Nakagawa, S., Nagata, K., Takebayashi, J., Nagashima, H., Tanaka, N., Kanai, K., Oda, T., Katayama, T., Furukawa, Y., Miyasaki, R., Noguchi, M., Hirose, K., Maezawa, H., Kano, H., Hirano, K., Ogino, M., Nishiwaki, K., Aoki, T., Morishita, T., Funatsu, K., Morita, A., Okazaki, I., Matsuzaki, S., Oda, M., Asakura, H., Kamegaya, K., Tsuchiya, M., Sambe, K., Kawakami, H., Kunimasa, T., Aimitsu, A., Yamashita, S., Miyoshi, A., Enzan, H., Ikehara, K., Shiozaki, Y., Sameshima, Y., Mizuno, T., Sasakawa, M., Nagi, S., Nagata, T., Fuwa, H., Tatsumi, K., Komatsu, K., Ozeki, T., Kaneda, M., Otsuki, M., Tadaki, H., Miura, K., Yamagata, S., Iwamura, K., Yamanaka, I., Sugimoto, E., Yamazaki, Y., Shiraishi, I., Yamanaka, T., Koike, H., Shimura, S., Hirayama, Y., Nishikawa, H., Kawamura, T., Kamiyama, Y., Takeda, H., Kamano, Y., Kitamura, O., Yamaoka, Y., Nanbu, H., Ozawa, K., Takasan, H., Honjo, I., Itakura, H., Akanuma, Y., Kagaya, T., Kaito, I., Sato, S., Sahara, H., Arisue, T., Kashimura, K., Motoyama, W., Hayashi, H., Okuyama, S., Ito, S., Inagaki, T., Kato, Y., Kakumu, S., Kurokawa, S., Yamawaki, T., Kusakabe, A., Hara, T., Funayama, A., Takahashi, T., Furuta, S., Omori, A., Hanaoka, S., Nagata, A., Tsukioka, J., Kiyosawa, K., Akahane, Y., Koike, Y., Oda, M., Tanaka, K., Kojima, M., Kawaguchi, Y., Kimura, A., Osamura, H., Kurihara, N., Okabe, K., Fujisawa, K., Takahashi, T., Kitami, N., Namihisa, T., Yamaguchi, K., Hisauchi, T., Nambu, M., Iijima, K., Rin, K., Kuroda, H., Kobayashi, N., Inami, Y., Shiga, K., Kon, T., Yamada, T., Yamada, T., Mizoguchi, Y., Enomoto, T., Monna, T., Yamamoto, S., Morisawa, S., Imoto, S., Uchita, K., Yamasawa, Y., Hiraide, S., Hikita, G., Takatsuki, K., Okimoto, Y., Nakagawa, J., Ito, K., Hirayama, C., Kawasaki, H., Irisa, T., Arimura, K., Amagase, H., Shibasaki, K., Tashiro, S., Ichida, F., Tozawa, T., Ishii, M., Inoue, E., Ikehara, H., Baba, S., Miyaji, Y., Nakajima, K., Shimizu, T., Shimizu, Y., Ohnishi, S., Sasaki, S., Kinami, Y., Mizukami, T., Nishida, Y., Nakagawa, T., Ojima, T., Takeshita, Y., Yamashita, T., Furuto, T., Ono, T., Yamaguchi, K., Mizuno, S., Tsumori, K., Miyagi, K., Suga, Y., Tatsumi, S., Kitano, A., Makiishi, H., Mitani, E., Mohri, S., Kamata, T., Kobayashi, K., Yamamoto, S., Yoshii, T., Takemoto, T., Suzuki, H., Hiratsuka, H., Takada, K., Maruyama, M., Takemoto, T., Suzuki, H., Katsu, K., Nomura, M., Kiyama, T., Hirabayashi, H., Yamashita, H., Masuyama, S., Takehara, Y., Sato, T., Abe, H., Sugiura, M., Shima, F., Ichihara, S., Yamasaki, Z., Fukuzawa, S., Horiguchi, Y., Takeda, T., Nakano, S., Kitamura, K., Miwa, M., Suzuke, T., Okada, K., Nakamura, T., Kikuchi, T., Mishima, K., Mandai, M., Kondo, H., Yamagata, Y., Uchida, Y., Harada, H., Nishizawa, M., Nomoto, K., Kariya, A., Ueno, M., Hayashi, M., Kobayashi, S., Mizuno, K., Shinozuka, T., Maruyama, T., Ogiwara, T., Okui, K., Miyake, N., Okada, M., Takahashi, K., Koizumi, H., Hayashi, T., Maeda, H., Abe, M., Takahashi, I., Matsumoto, M., Unoura, T., Iwasaki, A., Hattori, T., Tanaka, M., Hara, T., Sato, H., Hirashima, T., Shioda, A., Kawamura, I., Muto, M., Tsuchiya, R., Sato, Y., Ozawa, T., Hatano, T., Arae, H., Sekine, T., Tsukamoto, M., Shiratori, T., Asaki, S., Oba, E., Yamagata, H., Kobiyama, M., Hisamichi, S., Kitagawa, M., Kobayashi, N., Kurosawa, T., Tokimatsu, S., Kawasaki, S., Iwasa, A., Nagashima, K., Kodeki, K., Hoshizawa, T., Murakami, H., Yagi, T., Matsuda, T., Iwazaki, T., Suzuki, Y., Taketomi, H., Akaike, Y., Naramoto, J., Tsuru, T., Inoue, M., Nagase, T., Kato, K., and Kohyama, K.
Published: 1973
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14. Integrative Annotation of 21,037 Human Genes\ud Validated by Full-Length cDNA Clones

Author: Imanishi, T., Itoh, T., Suzuki, Y., O'Donovan, C., Fukuchi, S., Koyanagi, K.O., Barrero, R.A., Tamura, T., Yamaguchi-Kabata, Y., Tanino, M., Yura, K., Miyazaki, S., Ikeo, K., Homma, K., Kasprzyk, A., Nishikawa, T., Hirakawa, M., Thierry-Mieg, J., Thierry-Mieg, D., Ashurst, J., Jia, L., Nakao, M., Thomas, M.A., Mulder, N., Karavidopoulou, Y., Jin, L., Kim, S., Yasuda, T., Lenhard, B., Eveno, E., Yamasaki, C., Takeda, J., Gough, C., Hilton, P., Fujii, Y., Sakai, H., Tanaka, S., Amid, C., Bellgard, M., De Fatima Bonaldo, M., Bono, H., Bromberg, S.K., Brookes, A.J., Bruford, E., Carninci, P., Chelala, C., Couillault, C., de Souza, S.J., Debily, M., Devignes, M., Dubchak, I., Endo, T., Estreicher, A., Eyras, E., Fukami-Kobayashi, K., Gopinath, G.R., Graudens, E., Hahn, Y., Han, M., Han, Z., Hanada, K., Hanaoka, H., Harada, E., Hinz, U., Hishiki, T., Hopkinson, I., Imbeaud, S., Inoko, H., Kanapin, A., Kaneko, Y., Kasukawa, T., Kersey, P., Kikuno, R., Kimura, K., Korn, B., Kuryshev, V., Makalowska, I., Makino, T., Mano, S., Mariage-Samson, R., Mashima, J., Matsuda, H., Mewes, H., Minoshima, S., Nagai, K., Nagasaki, H., Nagata, N., Nigam, R., Ogasawara, O., Ohara, O., Ohtsubo, M., Okido, T., Oota, S., Ota, M., Ota, T., Otsuki, T., Piatier-Tonneau, D., Poustka, A., Ren, S., Saitou, N., Sakai, K., Sakamoto, S., Sakate, R., Schupp, I., Servant, F., Sherry, S., Shiba, R., Shimizu, N., Shimoyama, M., Simpson, A.J., Soares, B., Steward, C., Suwa, M., Suzuki, M., Takahashi, A., Tamiya, G., Tanaka, H., Taylor, T., Terwilliger, J.D., Unneberg, P., Veeramachaneni, V., Watanabe, S., Wilming, L., Yasuda, N., Yoo, H-S., Stodolsky, M., Makalowski, W., Go, M., Nakai, K., Takagi, T., Kanehisa, M., Sakaki, Y., Quackenbush, J., Okazaki, Y., Hayashizaki, Y., Hide, W., Chakraborty, R., Nishikawa, K., Sugawara, H., Tateno, Y., Chen, Z., Oishi, M., Tonellato, P., Apweiler, R., Okubo, K., Wagner, L., Wiemann, S., Strausberg, R.L., Isogai, T., Auffray, C., Nomura, N., Gojobori, T., and Sugano, S.
Abstract: The human genome sequence defines our inherent biological potential; the realization of the biology encoded therein\ud requires knowledge of the function of each gene. Currently, our knowledge in this area is still limited. Several lines of\ud investigation have been used to elucidate the structure and function of the genes in the human genome. Even so, gene\ud prediction remains a difficult task, as the varieties of transcripts of a gene may vary to a great extent. We thus\ud performed an exhaustive integrative characterization of 41,118 full-length cDNAs that capture the gene transcripts as\ud complete functional cassettes, providing an unequivocal report of structural and functional diversity at the gene level.\ud Our international collaboration has validated 21,037 human gene candidates by analysis of high-quality full-length\ud cDNA clones through curation using unified criteria. This led to the identification of 5,155 new gene candidates. It also\ud manifested the most reliable way to control the quality of the cDNA clones. We have developed a human gene\ud database, called the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/). It provides the following:\ud integrative annotation of human genes, description of gene structures, details of novel alternative splicing isoforms,\ud non-protein-coding RNAs, functional domains, subcellular localizations, metabolic pathways, predictions of protein\ud three-dimensional structure, mapping of known single nucleotide polymorphisms (SNPs), identification of polymorphic\ud microsatellite repeats within human genes, and comparative results with mouse full-length cDNAs. The H-InvDB\ud analysis has shown that up to 4% of the human genome sequence (National Center for Biotechnology Information\ud build 34 assembly) may contain misassembled or missing regions. We found that 6.5% of the human gene candidates\ud (1,377 loci) did not have a good protein-coding open reading frame, of which 296 loci are strong candidates for nonprotein-coding\ud RNA genes. In addition, among 72,027 uniquely mapped SNPs and insertions/deletions localized within\ud human genes, 13,215 nonsynonymous SNPs, 315 nonsense SNPs, and 452 indels occurred in coding regions. Together\ud with 25 polymorphic microsatellite repeats present in coding regions, they may alter protein structure, causing\ud phenotypic effects or resulting in disease. The H-InvDB platform represents a substantial contribution to resources\ud needed for the exploration of human biology and pathology
Published: 2004

15. GP2-7: The IGF/IGFR pathway regulates axial patterning during early neural development in mammal

Author: Takata, N., primary, Sakakura, E., additional, Kasukawa, T., additional, Eiraku, M., additional, and Sasai, Y., additional
Published: 2014
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16. Analysis of the mouse transcriptome based on functional annotation of 60, 770 full-length cDNAs

Author: Okazaki, Y., Furuno, M., Kasukawa, T., Adachi, J., Bono, H., Kondo, S., Nikaido, I., Osato, N., Saito, R., Suzuki, H., Yamanaka, I., Kiyosawa, H., Yagi, K., Tomaru, Y., Hasegawa, Y., Nogami, A., Schonbach, C., and Lenhard, Boris
Subjects: genom miša, transkriptom miša
Abstract: Only a small proportion of the mouse genome is transcribed into mature messenger RNA transcripts. There is an international collaborative effort to identify all full-length mRNA transcripts from the mouse, and to ensure that each is represented in a physical collection of clones. Here we report the manual annotation of 60, 770 full-length mouse complementary DNA sequences. These are clustered into 33, 409 'transcriptional units', contributing 90.1% of a newly established mouse transcriptome database. Of these transcriptional units, 4, 258 are new protein-coding and 11, 665 are new non-coding messages, indicating that non-coding RNA is a major component of the transcriptome. 41% of all transcriptional units showed evidence of alternative splicing. In protein-coding transcripts, 79% of splice variations altered the protein product. Whole-transcriptome analyses resulted in the identification of 2, 431 sense-antisense pairs. The present work, completely supported by physical clones, provides the most comprehensive survey of a mammalian transcriptome so far, and is a valuable resource for functional genomics
Published: 2002

17. Analysis of the mouse transcriptome based on functional annotation of 60,770 full-length cDNAs

Author: Okazaki, Y, Furuno, M, Kasukawa, T, Adachi, J, Bono, H, Schneider, Claudio, Fantom, C, and RIKEN GENOME EXPLORATION RESEARCH GROUP
Published: 2002

18. Alternate transcription of the Toll-like receptor signaling cascade

Author: Wells, CA, Chalk, AM, Forrest, A, Taylor, D, Waddell, N, Schroder, K, Himes, SR, Faulkner, G, Lo, S, Kasukawa, T, Kawaji, H, Kai, C, Kawai, J, Katayama, S, Carninci, P, Hayashizaki, Y, Hume, DA, Grimmond, SM, Wells, CA, Chalk, AM, Forrest, A, Taylor, D, Waddell, N, Schroder, K, Himes, SR, Faulkner, G, Lo, S, Kasukawa, T, Kawaji, H, Kai, C, Kawai, J, Katayama, S, Carninci, P, Hayashizaki, Y, Hume, DA, and Grimmond, SM
Abstract: BACKGROUND: Alternate splicing of key signaling molecules in the Toll-like receptor (Tlr) cascade has been shown to dramatically alter the signaling capacity of inflammatory cells, but it is not known how common this mechanism is. We provide transcriptional evidence of widespread alternate splicing in the Toll-like receptor signaling pathway, derived from a systematic analysis of the FANTOM3 mouse data set. Functional annotation of variant proteins was assessed in light of inflammatory signaling in mouse primary macrophages, and the expression of each variant transcript was assessed by splicing arrays. RESULTS: A total of 256 variant transcripts were identified, including novel variants of Tlr4, Ticam1, Tollip, Rac1, Irak1, 2 and 4, Mapk14/p38, Atf2 and Stat1. The expression of variant transcripts was assessed using custom-designed splicing arrays. We functionally tested the expression of Tlr4 transcripts under a range of cytokine conditions via northern and quantitative real-time polymerase chain reaction. The effects of variant Mapk14/p38 protein expression on macrophage survival were demonstrated. CONCLUSION: Members of the Toll-like receptor signaling pathway are highly alternatively spliced, producing a large number of novel proteins with the potential to functionally alter inflammatory outcomes. These variants are expressed in primary mouse macrophages in response to inflammatory mediators such as interferon-gamma and lipopolysaccharide. Our data suggest a surprisingly common role for variant proteins in diversification/repression of inflammatory signaling.
Published: 2006

19. Differential use of signal peptides and membrane domains is a common occurrence in the protein output of transcriptional units

Author: Blake, J, Hancock, J, Pavan, B, Stubbs, L, Davis, MJ, Hanson, KA, Clark, F, Fink, JL, Zhang, F, Kasukawa, T, Kai, C, Kawai, J, Carninci, P, Hayashizaki, Y, Teasdale, RD, Blake, J, Hancock, J, Pavan, B, Stubbs, L, Davis, MJ, Hanson, KA, Clark, F, Fink, JL, Zhang, F, Kasukawa, T, Kai, C, Kawai, J, Carninci, P, Hayashizaki, Y, and Teasdale, RD
Abstract: Membrane organization describes the orientation of a protein with respect to the membrane and can be determined by the presence, or absence, and organization within the protein sequence of two features: endoplasmic reticulum signal peptides and alpha-helical transmembrane domains. These features allow protein sequences to be classified into one of five membrane organization categories: soluble intracellular proteins, soluble secreted proteins, type I membrane proteins, type II membrane proteins, and multi-spanning membrane proteins. Generation of protein isoforms with variable membrane organizations can change a protein's subcellular localization or association with the membrane. Application of MemO, a membrane organization annotation pipeline, to the FANTOM3 Isoform Protein Sequence mouse protein set revealed that within the 8,032 transcriptional units (TUs) with multiple protein isoforms, 573 had variation in their use of signal peptides, 1,527 had variation in their use of transmembrane domains, and 615 generated protein isoforms from distinct membrane organization classes. The mechanisms underlying these transcript variations were analyzed. While TUs were identified encoding all pairwise combinations of membrane organization categories, the most common was conversion of membrane proteins to soluble proteins. Observed within our high-confidence set were 156 TUs predicted to generate both extracellular soluble and membrane proteins, and 217 TUs generating both intracellular soluble and membrane proteins. The differential use of endoplasmic reticulum signal peptides and transmembrane domains is a common occurrence within the variable protein output of TUs. The generation of protein isoforms that are targeted to multiple subcellular locations represents a major functional consequence of transcript variation within the mouse transcriptome.
Published: 2006

20. Transcript annotation in FANTOM3:: Mouse gene catalog based on physical cDNAs

Author: Maeda, N, Kasukawa, T, Oyama, R, Gough, J, Frith, M, Engstrom, PG, Lenhard, B, Aturaliya, RN, Batalov, S, Beisel, KW, Bult, CJ, Fletcher, CF, Forrest, ARR, Furuno, M, Hill, D, Itoh, M, Kanamori-Katayama, M, Katayama, S, Katoh, M, Kawashima, T, Quackenbush, J, Ravasi, T, Ring, BZ, Shibata, K, Sugiura, K, Takenaka, Y, Teasdale, RD, Wells, CA, Zhu, Y, Kai, C, Kawai, J, Hume, DA, Carninci, P, Hayashizaki, Y, Maeda, N, Kasukawa, T, Oyama, R, Gough, J, Frith, M, Engstrom, PG, Lenhard, B, Aturaliya, RN, Batalov, S, Beisel, KW, Bult, CJ, Fletcher, CF, Forrest, ARR, Furuno, M, Hill, D, Itoh, M, Kanamori-Katayama, M, Katayama, S, Katoh, M, Kawashima, T, Quackenbush, J, Ravasi, T, Ring, BZ, Shibata, K, Sugiura, K, Takenaka, Y, Teasdale, RD, Wells, CA, Zhu, Y, Kai, C, Kawai, J, Hume, DA, Carninci, P, and Hayashizaki, Y
Abstract: The international FANTOM consortium aims to produce a comprehensive picture of the mammalian transcriptome, based upon an extensive cDNA collection and functional annotation of full-length enriched cDNAs. The previous dataset, FANTOM2, comprised 60,770 full-length enriched cDNAs. Functional annotation revealed that this cDNA dataset contained only about half of the estimated number of mouse protein-coding genes, indicating that a number of cDNAs still remained to be collected and identified. To pursue the complete gene catalog that covers all predicted mouse genes, cloning and sequencing of full-length enriched cDNAs has been continued since FANTOM2. In FANTOM3, 42,031 newly isolated cDNAs were subjected to functional annotation, and the annotation of 4,347 FANTOM2 cDNAs was updated. To accomplish accurate functional annotation, we improved our automated annotation pipeline by introducing new coding sequence prediction programs and developed a Web-based annotation interface for simplifying the annotation procedures to reduce manual annotation errors. Automated coding sequence and function prediction was followed with manual curation and review by expert curators. A total of 102,801 full-length enriched mouse cDNAs were annotated. Out of 102,801 transcripts, 56,722 were functionally annotated as protein coding (including partial or truncated transcripts), providing to our knowledge the greatest current coverage of the mouse proteome by full-length cDNAs. The total number of distinct non-protein-coding transcripts increased to 34,030. The FANTOM3 annotation system, consisting of automated computational prediction, manual curation, and final expert curation, facilitated the comprehensive characterization of the mouse transcriptome, and could be applied to the transcriptomes of other species.
Published: 2006

21. Development and Evaluation of an Automated Annotation Pipeline and cDNA Annotation System

Author: Kasukawa, T., primary
Published: 2003
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22. Human genome meeting 2016

Author: Srivastava, A., Wang, Y., Huang, R., Skinner, C., Thompson, T., Pollard, L., Wood, T., Luo, F., Stevenson, R., Polimanti, R., Gelernter, J., Lin, X., Lim, I., Wu, Y., Teh, A., Chen, L., Aris, I., Soh, S., Tint, M., MacIsaac, J., Yap, F., Kwek, K., Saw, S., Kobor, M., Meaney, M., Godfrey, K., Chong, Y., Holbrook, J., Lee, Y., Gluckman, P., Karnani, N., Kapoor, A., Lee, D., Chakravarti, A., Maercker, C., Graf, F., Boutros, M., Stamoulis, G., Santoni, F., Makrythanasis, P., Letourneau, A., Guipponi, M., Panousis, N., Garieri, M., Ribaux, P., Falconnet, E., Borel, C., Antonarakis, S., Kumar, S., Curran, J., Blangero, J., Chatterjee, S., Kapoor, A., Akiyama, J., Auer, D., Berrios, C., Pennacchio, L., Chakravarti, A., Donti, T., Cappuccio, G., Miller, M., Atwal, P., Kennedy, A., Cardon, A., Bacino, C., Emrick, L., Hertecant, J., Baumer, F., Porter, B., Bainbridge, M., Bonnen, P., Graham, B., Sutton, R., Sun, Q., Elsea, S., Hu, Z., Wang, P., Zhu, Y., Zhao, J., Xiong, M., Bennett, David, Hidalgo-Miranda, A., Romero-Cordoba, S., Rodriguez-Cuevas, S., Rebollar-Vega, R., Tagliabue, E., Iorio, M., D’Ippolito, E., Baroni, S., Kaczkowski, B., Tanaka, Y., Kawaji, H., Sandelin, A., Andersson, R., Itoh, M., Lassmann, T., Hayashizaki, Y., Carninci, P., Forrest, A., Semple, C., Rosenthal, E., Shirts, B., Amendola, L., Gallego, C., Horike-Pyne, M., Burt, A., Robertson, P., Beyers, P., Nefcy, C., Veenstra, D., Hisama, F., Bennett, R., Dorschner, M., Nickerson, D., Smith, J., Patterson, K., Crosslin, D., Nassir, R., Zubair, N., Harrison, T., Peters, U., Jarvik, G., Menghi, F., Inaki, K., Woo, X., Kumar, P., Grzeda, K., Malhotra, A., Kim, H., Ucar, D., Shreckengast, P., Karuturi, K., Keck, J., Chuang, J., Liu, E., Ji, B., Tyler, A., Ananda, G., Carter, G., Nikbakht, H., Montagne, M., Zeinieh, M., Harutyunyan, A., Mcconechy, M., Jabado, N., Lavigne, P., Majewski, J., Goldstein, J., Overman, M., Varadhachary, G., Shroff, R., Wolff, R., Javle, M., Futreal, A., Fogelman, D., Bravo, L., Fajardo, W., Gomez, H., Castaneda, C., Rolfo, C., Pinto, J., Akdemir, K., Chin, L., Futreal, A., Patterson, S., Statz, C., Mockus, S., Nikolaev, S., Bonilla, X., Parmentier, L., King, B., Bezrukov, F., Kaya, G., Zoete, V., Seplyarskiy, V., Sharpe, H., McKee, T., Letourneau, A., Ribaux, P., Popadin, K., Basset-Seguin, N., Chaabene, R., Santoni, F., Andrianova, M., Guipponi, M., Garieri, M., Verdan, C., Grosdemange, K., Sumara, O., Eilers, M., Aifantis, I., Michielin, O., de Sauvage, F., Antonarakis, S., Likhitrattanapisal, S., Lincoln, S., Kurian, A., Desmond, A., Yang, S., Kobayashi, Y., Ford, J., Ellisen, L., Peters, T., Alvarez, K., Hollingsworth, E., Lopez-Terrada, D., Hastie, A., Dzakula, Z., Pang, A., Lam, E., Anantharaman, T., Saghbini, M., Cao, H., Gonzaga-Jauregui, C., Ma, L., King, A., Rosenzweig, E., Krishnan, U., Reid, J., Overton, J., Dewey, F., Chung, W., Small, K., DeLuca, A., Cremers, F., Lewis, R., Puech, V., Bakall, B., Silva-Garcia, R., Rohrschneider, K., Leys, M., Shaya, F., Stone, E., Sobreira, N., Schiettecatte, F., Ling, H., Pugh, E., Witmer, D., Hetrick, K., Zhang, P., Doheny, K., Valle, D., Hamosh, A., Jhangiani, S., Akdemir, Z., Bainbridge, M., Charng, W., Wiszniewski, W., Gambin, T., Karaca, E., Bayram, Y., Eldomery, M., Posey, J., Doddapaneni, H., Hu, J., Sutton, V., Muzny, D., Boerwinkle, E., Valle, D., Lupski, J., Gibbs, R., Shekar, S., Salerno, W., English, A., Mangubat, A., Bruestle, J., Thorogood, A., Knoppers, B., Takahashi, H., Nitta, K., Kozhuharova, A., Suzuki, A., Sharma, H., Cotella, D., Santoro, C., Zucchelli, S., Gustincich, S., Carninci, P., Mulvihill, J., Baynam, G., Gahl, W., Groft, S., Kosaki, K., Lasko, P., Melegh, B., Taruscio, D., Ghosh, R., Plon, S., Scherer, S., Qin, X., Sanghvi, R., Walker, K., Chiang, T., Muzny, D., Wang, L., Black, J., Boerwinkle, E., Weinshilboum, R., Gibbs, R., Karpinets, T., Calderone, T., Wani, K., Yu, X., Creasy, C., Haymaker, C., Forget, M., Nanda, V., Roszik, J., Wargo, J., Haydu, L., Song, X., Lazar, A., Gershenwald, J., Davies, M., Bernatchez, C., Zhang, J., Futreal, A., Woodman, S., Chesler, E., Reynolds, T., Bubier, J., Phillips, C., Langston, M., Baker, E., Xiong, M., Ma, L., Lin, N., Amos, C., Lin, N., Wang, P., Zhu, Y., Zhao, J., Calhoun, V., Xiong, M., Dobretsberger, O., Egger, M., Leimgruber, F., Sadedin, S., Oshlack, A., Antonio, V., Ono, N., Ahmed, Z., Bolisetty, M., Zeeshan, S., Anguiano, E., Ucar, D., Sarkar, A., Nandineni, M., Zeng, C., Shao, J., Cao, H., Hastie, A., Pang, A., Lam, E., Liang, T., Pham, K., Saghbini, M., Dzakula, Z., Chee-Wei, Y., Dongsheng, L., Lai-Ping, W., Lian, D., Hee, R., Yunus, Y., Aghakhanian, F., Mokhtar, S., Lok-Yung, C., Bhak, J., Phipps, M., Shuhua, X., Yik-Ying, T., Kumar, V., Boon-Peng, H., Campbell, I., Young, M., James, P., Rain, M., Mohammad, G., Kukreti, R., Pasha, Q., Akilzhanova, A., Guelly, C., Abilova, Z., Rakhimova, S., Akhmetova, A., Kairov, U., Trajanoski, S., Zhumadilov, Z., Bekbossynova, M., Schumacher, C., Sandhu, S., Harkins, T., Makarov, V., Doddapaneni, H., Glenn, R., Momin, Z., Dilrukshi, B., Chao, H., Meng, Q., Gudenkauf, B., Kshitij, R., Jayaseelan, J., Nessner, C., Lee, S., Blankenberg, K., Lewis, L., Hu, J., Han, Y., Dinh, H., Jireh, S., Walker, K., Boerwinkle, E., Muzny, D., Gibbs, R., Hu, J., Walker, K., Buhay, C., Liu, X., Wang, Q., Sanghvi, R., Doddapaneni, H., Ding, Y., Veeraraghavan, N., Yang, Y., Boerwinkle, E., Beaudet, A., Eng, C., Muzny, D., Gibbs, R., Worley, K., Liu, Y., Hughes, D., Murali, S., Harris, R., English, A., Qin, X., Hampton, O., Larsen, P., Beck, C., Han, Y., Wang, M., Doddapaneni, H., Kovar, C., Salerno, W., Yoder, A., Richards, S., Rogers, J., Lupski, J., Muzny, D., Gibbs, R., Meng, Q., Bainbridge, M., Wang, M., Doddapaneni, H., Han, Y., Muzny, D., Gibbs, R., Harris, R., Raveenedran, M., Xue, C., Dahdouli, M., Cox, L., Fan, G., Ferguson, B., Hovarth, J., Johnson, Z., Kanthaswamy, S., Kubisch, M., Platt, M., Smith, D., Vallender, E., Wiseman, R., Liu, X., Below, J., Muzny, D., Gibbs, R., Yu, F., Rogers, J., Lin, J., Zhang, Y., Ouyang, Z., Moore, A., Wang, Z., Hofmann, J., Purdue, M., Stolzenberg-Solomon, R., Weinstein, S., Albanes, D., Liu, C., Cheng, W., Lin, T., Lan, Q., Rothman, N., Berndt, S., Chen, E., Bahrami, H., Khoshzaban, A., Keshal, S., Bahrami, H., Khoshzaban, A., Keshal, S., Alharbi, K., Zhalbinova, M., Akilzhanova, A., Rakhimova, S., Bekbosynova, M., Myrzakhmetova, S., Matar, M., Mili, N., Molinari, R., Ma, Y., Guerrier, S., Elhawary, N., Tayeb, M., Bogari, N., Qotb, N., McClymont, S., Hook, P., Goff, L., McCallion, A., Kong, Y., Charette, J., Hicks, W., Naggert, J., Zhao, L., Nishina, P., Edrees, B., Athar, M., Al-Allaf, F., Taher, M., Khan, W., Bouazzaoui, A., Harbi, N., Safar, R., Al-Edressi, H., Anazi, A., Altayeb, N., Ahmed, M., Alansary, K., Abduljaleel, Z., Kratz, A., Beguin, P., Poulain, S., Kaneko, M., Takahiko, C., Matsunaga, A., Kato, S., Suzuki, A., Bertin, N., Lassmann, T., Vigot, R., Carninci, P., Plessy, C., Launey, T., Graur, D., Lee, D., Kapoor, A., Chakravarti, A., Friis-Nielsen, J., Izarzugaza, J., Brunak, S., Chakraborty, A., Basak, J., Mukhopadhyay, A., Soibam, B., Das, D., Biswas, N., Das, S., Sarkar, S., Maitra, A., Panda, C., Majumder, P., Morsy, H., Gaballah, A., Samir, M., Shamseya, M., Mahrous, H., Ghazal, A., Arafat, W., Hashish, M., Gruber, J., Jaeger, N., Snyder, M., Patel, K., Bowman, S., Davis, T., Kraushaar, D., Emerman, A., Russello, S., Henig, N., Hendrickson, C., Zhang, K., Rodriguez-Dorantes, M., Cruz-Hernandez, C., Garcia-Tobilla, C., Solorzano-Rosales, S., Jäger, N., Chen, J., Haile, R., Hitchins, M., Brooks, J., Snyder, M., Jiménez-Morales, S., Ramírez, M., Nuñez, J., Bekker, V., Leal, Y., Jiménez, E., Medina, A., Hidalgo, A., Mejía, J., Halytskiy, V., Naggert, J., Collin, G., DeMauro, K., Hanusek, R., Nishina, P., Belhassa, K., Belhassan, K., Bouguenouch, L., Samri, I., Sayel, H., moufid, FZ., El Bouchikhi, I., Trhanint, S., Hamdaoui, H., Elotmani, I., Khtiri, I., Kettani, O., Quibibo, L., Ahagoud, M., Abbassi, M., Ouldim, K., Marusin, A., Kornetov, A., Swarovskaya, M., Vagaiceva, K., Stepanov, V., De La Paz, E., Sy, R., Nevado, J., Reganit, P., Santos, L., Magno, J., Punzalan, F., Ona, D., Llanes, E., Santos-Cortes, R., Tiongco, R., Aherrera, J., Abrahan, L., Pagauitan-Alan, P., Morelli, K., Domire, J., Pyne, N., Harper, S., Burgess, R., Zhalbinova, M., Akilzhanova, A., Rakhimova, S., Bekbosynova, M., Myrzakhmetova, S., Gari, M., Dallol, A., Alsehli, H., Gari, A., Gari, M., Abuzenadah, A., Thomas, M., Sukhai, M., Garg, S., Misyura, M., Zhang, T., Schuh, A., Stockley, T., Kamel-Reid, S., Sherry, S., Xiao, C., Slotta, D., Rodarmer, K., Feolo, M., Kimelman, M., Godynskiy, G., O’Sullivan, C., Yaschenko, E., Xiao, C., Yaschenko, E., Sherry, S., Rangel-Escareño, C., Rueda-Zarate, H., Tayubi, I., Mohammed, R., Ahmed, I., Ahmed, T., Seth, S., Amin, S., Song, X., Mao, X., Sun, H., Verhaak, R., Futreal, A., Zhang, J., Whiite, S., Chiang, T., English, A., Farek, J., Kahn, Z., Salerno, W., Veeraraghavan, N., Boerwinkle, E., Gibbs, R., Kasukawa, T., Lizio, M., Harshbarger, J., Hisashi, S., Severin, J., Imad, A., Sahin, S., Freeman, T., Baillie, K., Sandelin, A., Carninci, P., Forrest, A., Kawaji, H., Salerno, W., English, A., Shekar, S., Mangubat, A., Bruestle, J., Boerwinkle, E., Gibbs, R., Salem, A., Ali, M., Ibrahim, A., Ibrahim, M., Barrera, H., Garza, L., Torres, J., Barajas, V., Ulloa-Aguirre, A., Kershenobich, D., Mortaji, Shahroj, Guizar, Pedro, Loera, Eliezer, Moreno, Karen, De León, Adriana, Monsiváis, Daniela, Gómez, Jackeline, Cardiel, Raquel, Fernandez-Lopez, J., Bonifaz-Peña, V., Rangel-Escareño, C., Hidalgo-Miranda, A., Contreras, A., Polfus, L., Wang, X., Philip, V., Carter, G., Abuzenadah, A., Gari, M., Turki, R., Dallol, A., Uyar, A., Kaygun, A., Zaman, S., Marquez, E., George, J., Ucar, D., Hendrickson, C., Emerman, A., Kraushaar, D., Bowman, S., Henig, N., Davis, T., Russello, S., Patel, K., Starr, D., Baird, M., Kirkpatrick, B., Sheets, K., Nitsche, R., Prieto-Lafuente, L., Landrum, M., Lee, J., Rubinstein, W., Maglott, D., Thavanati, P., de Dios, A., Hernandez, R., Aldrate, M., Mejia, M., Kanala, K., Abduljaleel, Z., Khan, W., Al-Allaf, F., Athar, M., Taher, M., Shahzad, N., Bouazzaoui, A., Huber, E., Dan, A., Al-Allaf, F., Herr, W., Sprotte, G., Köstler, J., Hiergeist, A., Gessner, A., Andreesen, R., Holler, E., Al-Allaf, F., Alashwal, A., Abduljaleel, Z., Taher, M., Bouazzaoui, A., Abalkhail, H., Al-Allaf, A., Bamardadh, R., Athar, M., Filiptsova, O., Kobets, M., Kobets, Y., Burlaka, I., Timoshyna, I., Filiptsova, O., Kobets, M., Kobets, Y., Burlaka, I., Timoshyna, I., Filiptsova, O., Kobets, M., Kobets, Y., Burlaka, I., Timoshyna, I., Al-allaf, F., Mohiuddin, M., Zainularifeen, A., Mohammed, A., Abalkhail, H., Owaidah, T., and Bouazzaoui, A.
Abstract: O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents R. Polimanti, J. Gelernter O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus A. Kapoor, D. Lee, A. Chakravarti O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells C. Maercker, F. Graf, M. Boutros O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis O7 Role of microRNA in LCL to IPSC reprogramming S. Kumar, J. Curran, J. Blangero O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti O9 Metabolomic profiling for the diagnosis of neurometabolic disorders T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea O10 A novel causal methylation network approach to Alzheimer’s disease Z. Hu, P. Wang, Y. Zhu, J. Zhao, M. Xiong, David A Bennett O11 A microRNA signature identifies subtypes of triple-negative breast cancer and reveals MIR-342-3P as regulator of a lactate metabolic pathway A. Hidalgo-Miranda, S. Romero-Cordoba, S. Rodriguez-Cuevas, R. Rebollar-Vega, E. Tagliabue, M. Iorio, E. D’Ippolito, S. Baroni O12 Transcriptome analysis identifies genes, enhancer RNAs and repetitive elements that are recurrently deregulated across multiple cancer types B. Kaczkowski, Y. Tanaka, H. Kawaji, A. Sandelin, R. Andersson, M. Itoh, T. Lassmann, the FANTOM5 consortium, Y. Hayashizaki, P. Carninci, A. R. R. Forrest O13 Elevated mutation and widespread loss of constraint at regulatory and architectural binding sites across 11 tumour types C. A. Semple O14 Exome sequencing provides evidence of pathogenicity for genes implicated in colorectal cancer E. A. Rosenthal, B. Shirts, L. Amendola, C. Gallego, M. Horike-Pyne, A. Burt, P. Robertson, P. Beyers, C. Nefcy, D. Veenstra, F. Hisama, R. Bennett, M. Dorschner, D. Nickerson, J. Smith, K. Patterson, D. Crosslin, R. Nassir, N. Zubair, T. Harrison, U. Peters, G. Jarvik, NHLBI GO Exome Sequencing Project O15 The tandem duplicator phenotype as a distinct genomic configuration in cancer F. Menghi, K. Inaki, X. Woo, P. Kumar, K. Grzeda, A. Malhotra, H. Kim, D. Ucar, P. Shreckengast, K. Karuturi, J. Keck, J. Chuang, E. T. Liu O16 Modeling genetic interactions associated with molecular subtypes of breast cancer B. Ji, A. Tyler, G. Ananda, G. Carter O17 Recurrent somatic mutation in the MYC associated factor X in brain tumors H. Nikbakht, M. Montagne, M. Zeinieh, A. Harutyunyan, M. Mcconechy, N. Jabado, P. Lavigne, J. Majewski O18 Predictive biomarkers to metastatic pancreatic cancer treatment J. B. Goldstein, M. Overman, G. Varadhachary, R. Shroff, R. Wolff, M. Javle, A. Futreal, D. Fogelman O19 DDIT4 gene expression as a prognostic marker in several malignant tumors L. Bravo, W. Fajardo, H. Gomez, C. Castaneda, C. Rolfo, J. A. Pinto O20 Spatial organization of the genome and genomic alterations in human cancers K. C. Akdemir, L. Chin, A. Futreal, ICGC PCAWG Structural Alterations Group O21 Landscape of targeted therapies in solid tumors S. Patterson, C. Statz, S. Mockus O22 Genomic analysis reveals novel drivers and progression pathways in skin basal cell carcinoma S. N. Nikolaev, X. I. Bonilla, L. Parmentier, B. King, F. Bezrukov, G. Kaya, V. Zoete, V. Seplyarskiy, H. Sharpe, T. McKee, A. Letourneau, P. Ribaux, K. Popadin, N. Basset-Seguin, R. Ben Chaabene, F. Santoni, M. Andrianova, M. Guipponi, M. Garieri, C. Verdan, K. Grosdemange, O. Sumara, M. Eilers, I. Aifantis, O. Michielin, F. de Sauvage, S. Antonarakis O23 Identification of differential biomarkers of hepatocellular carcinoma and cholangiocarcinoma via transcriptome microarray meta-analysis S. Likhitrattanapisal O24 Clinical validity and actionability of multigene tests for hereditary cancers in a large multi-center study S. Lincoln, A. Kurian, A. Desmond, S. Yang, Y. Kobayashi, J. Ford, L. Ellisen O25 Correlation with tumor ploidy status is essential for correct determination of genome-wide copy number changes by SNP array T. L. Peters, K. R. Alvarez, E. F. Hollingsworth, D. H. Lopez-Terrada O26 Nanochannel based next-generation mapping for interrogation of clinically relevant structural variation A. Hastie, Z. Dzakula, A. W. Pang, E. T. Lam, T. Anantharaman, M. Saghbini, H. Cao, BioNano Genomics O27 Mutation spectrum in a pulmonary arterial hypertension (PAH) cohort and identification of associated truncating mutations in TBX4 C. Gonzaga-Jauregui, L. Ma, A. King, E. Berman Rosenzweig, U. Krishnan, J. G. Reid, J. D. Overton, F. Dewey, W. K. Chung O28 NORTH CAROLINA macular dystrophy (MCDR1): mutations found affecting PRDM13 K. Small, A. DeLuca, F. Cremers, R. A. Lewis, V. Puech, B. Bakall, R. Silva-Garcia, K. Rohrschneider, M. Leys, F. S. Shaya, E. Stone O29 PhenoDB and genematcher, solving unsolved whole exome sequencing data N. L. Sobreira, F. Schiettecatte, H. Ling, E. Pugh, D. Witmer, K. Hetrick, P. Zhang, K. Doheny, D. Valle, A. Hamosh O30 Baylor-Johns Hopkins Center for Mendelian genomics: a four year review S. N. Jhangiani, Z. Coban Akdemir, M. N. Bainbridge, W. Charng, W. Wiszniewski, T. Gambin, E. Karaca, Y. Bayram, M. K. Eldomery, J. Posey, H. Doddapaneni, J. Hu, V. R. Sutton, D. M. Muzny, E. A. Boerwinkle, D. Valle, J. R. Lupski, R. A. Gibbs O31 Using read overlap assembly to accurately identify structural genetic differences in an ashkenazi jewish trio S. Shekar, W. Salerno, A. English, A. Mangubat, J. Bruestle O32 Legal interoperability: a sine qua non for international data sharing A. Thorogood, B. M. Knoppers, Global Alliance for Genomics and Health - Regulatory and Ethics Working Group O33 High throughput screening platform of competent sineups: that can enhance translation activities of therapeutic target H. Takahashi, K. R. Nitta, A. Kozhuharova, A. M. Suzuki, H. Sharma, D. Cotella, C. Santoro, S. Zucchelli, S. Gustincich, P. Carninci O34 The undiagnosed diseases network international (UDNI): clinical and laboratory research to meet patient needs J. J. Mulvihill, G. Baynam, W. Gahl, S. C. Groft, K. Kosaki, P. Lasko, B. Melegh, D. Taruscio O36 Performance of computational algorithms in pathogenicity predictions for activating variants in oncogenes versus loss of function mutations in tumor suppressor genes R. Ghosh, S. Plon O37 Identification and electronic health record incorporation of clinically actionable pharmacogenomic variants using prospective targeted sequencing S. Scherer, X. Qin, R. Sanghvi, K. Walker, T. Chiang, D. Muzny, L. Wang, J. Black, E. Boerwinkle, R. Weinshilboum, R. Gibbs O38 Melanoma reprogramming state correlates with response to CTLA-4 blockade in metastatic melanoma T. Karpinets, T. Calderone, K. Wani, X. Yu, C. Creasy, C. Haymaker, M. Forget, V. Nanda, J. Roszik, J. Wargo, L. Haydu, X. Song, A. Lazar, J. Gershenwald, M. Davies, C. Bernatchez, J. Zhang, A. Futreal, S. Woodman O39 Data-driven refinement of complex disease classification from integration of heterogeneous functional genomics data in GeneWeaver E. J. Chesler, T. Reynolds, J. A. Bubier, C. Phillips, M. A. Langston, E. J. Baker O40 A general statistic framework for genome-based disease risk prediction M. Xiong, L. Ma, N. Lin, C. Amos O41 Integrative large-scale causal network analysis of imaging and genomic data and its application in schizophrenia studies N. Lin, P. Wang, Y. Zhu, J. Zhao, V. Calhoun, M. Xiong O42 Big data and NGS data analysis: the cloud to the rescue O. Dobretsberger, M. Egger, F. Leimgruber O43 Cpipe: a convergent clinical exome pipeline specialised for targeted sequencing S. Sadedin, A. Oshlack, Melbourne Genomics Health Alliance O44 A Bayesian classification of biomedical images using feature extraction from deep neural networks implemented on lung cancer data V. A. A. Antonio, N. Ono, Clark Kendrick C. Go O45 MAV-SEQ: an interactive platform for the Management, Analysis, and Visualization of sequence data Z. Ahmed, M. Bolisetty, S. Zeeshan, E. Anguiano, D. Ucar O47 Allele specific enhancer in EPAS1 intronic regions may contribute to high altitude adaptation of Tibetans C. Zeng, J. Shao O48 Nanochannel based next-generation mapping for structural variation detection and comparison in trios and populations H. Cao, A. Hastie, A. W. Pang, E. T. Lam, T. Liang, K. Pham, M. Saghbini, Z. Dzakula O49 Archaic introgression in indigenous populations of Malaysia revealed by whole genome sequencing Y. Chee-Wei, L. Dongsheng, W. Lai-Ping, D. Lian, R. O. Twee Hee, Y. Yunus, F. Aghakhanian, S. S. Mokhtar, C. V. Lok-Yung, J. Bhak, M. Phipps, X. Shuhua, T. Yik-Ying, V. Kumar, H. Boon-Peng O50 Breast and ovarian cancer prevention: is it time for population-based mutation screening of high risk genes? I. Campbell, M.-A. Young, P. James, Lifepool O53 Comprehensive coverage from low DNA input using novel NGS library preparation methods for WGS and WGBS C. Schumacher, S. Sandhu, T. Harkins, V. Makarov O54 Methods for large scale construction of robust PCR-free libraries for sequencing on Illumina HiSeqX platform H. DoddapaneniR. Glenn, Z. Momin, B. Dilrukshi, H. Chao, Q. Meng, B. Gudenkauf, R. Kshitij, J. Jayaseelan, C. Nessner, S. Lee, K. Blankenberg, L. Lewis, J. Hu, Y. Han, H. Dinh, S. Jireh, K. Walker, E. Boerwinkle, D. Muzny, R. Gibbs O55 Rapid capture methods for clinical sequencing J. Hu, K. Walker, C. Buhay, X. Liu, Q. Wang, R. Sanghvi, H. Doddapaneni, Y. Ding, N. Veeraraghavan, Y. Yang, E. Boerwinkle, A. L. Beaudet, C. M. Eng, D. M. Muzny, R. A. Gibbs O56 A diploid personal human genome model for better genomes from diverse sequence data K. C. C. Worley, Y. Liu, D. S. T. Hughes, S. C. Murali, R. A. Harris, A. C. English, X. Qin, O. A. Hampton, P. Larsen, C. Beck, Y. Han, M. Wang, H. Doddapaneni, C. L. Kovar, W. J. Salerno, A. Yoder, S. Richards, J. Rogers, J. R. Lupski, D. M. Muzny, R. A. Gibbs O57 Development of PacBio long range capture for detection of pathogenic structural variants Q. Meng, M. Bainbridge, M. Wang, H. Doddapaneni, Y. Han, D. Muzny, R. Gibbs O58 Rhesus macaques exhibit more non-synonymous variation but greater impact of purifying selection than humans R. A. Harris, M. Raveenedran, C. Xue, M. Dahdouli, L. Cox, G. Fan, B. Ferguson, J. Hovarth, Z. Johnson, S. Kanthaswamy, M. Kubisch, M. Platt, D. Smith, E. Vallender, R. Wiseman, X. Liu, J. Below, D. Muzny, R. Gibbs, F. Yu, J. Rogers O59 Assessing RNA structure disruption induced by single-nucleotide variation J. Lin, Y. Zhang, Z. Ouyang P1 A meta-analysis of genome-wide association studies of mitochondrial dna copy number A. Moore, Z. Wang, J. Hofmann, M. Purdue, R. Stolzenberg-Solomon, S. Weinstein, D. Albanes, C.-S. Liu, W.-L. Cheng, T.-T. Lin, Q. Lan, N. Rothman, S. Berndt P2 Missense polymorphic genetic combinations underlying down syndrome susceptibility E. S. Chen P4 The evaluation of alteration of ELAM-1 expression in the endometriosis patients H. Bahrami, A. Khoshzaban, S. Heidari Keshal P5 Obesity and the incidence of apolipoprotein E polymorphisms in an assorted population from Saudi Arabia population K. K. R. Alharbi P6 Genome-associated personalized antithrombotical therapy for patients with high risk of thrombosis and bleeding M. Zhalbinova, A. Akilzhanova, S. Rakhimova, M. Bekbosynova, S. Myrzakhmetova P7 Frequency of Xmn1 polymorphism among sickle cell carrier cases in UAE population M. Matar P8 Differentiating inflammatory bowel diseases by using genomic data: dimension of the problem and network organization N. Mili, R. Molinari, Y. Ma, S. Guerrier P9 Vulnerability of genetic variants to the risk of autism among Saudi children N. Elhawary, M. Tayeb, N. Bogari, N. Qotb P10 Chromatin profiles from ex vivo purified dopaminergic neurons establish a promising model to support studies of neurological function and dysfunction S. A. McClymont, P. W. Hook, L. A. Goff, A. McCallion P11 Utilization of a sensitized chemical mutagenesis screen to identify genetic modifiers of retinal dysplasia in homozygous Nr2e3rd7mice Y. Kong, J. R. Charette, W. L. Hicks, J. K. Naggert, L. Zhao, P. M. Nishina P12 Ion torrent next generation sequencing of recessive polycystic kidney disease in Saudi patients B. M. Edrees, M. Athar, F. A. Al-Allaf, M. M. Taher, W. Khan, A. Bouazzaoui, N. A. Harbi, R. Safar, H. Al-Edressi, A. Anazi, N. Altayeb, M. A. Ahmed, K. Alansary, Z. Abduljaleel P13 Digital expression profiling of Purkinje neurons and dendrites in different subcellular compartments A. Kratz, P. Beguin, S. Poulain, M. Kaneko, C. Takahiko, A. Matsunaga, S. Kato, A. M. Suzuki, N. Bertin, T. Lassmann, R. Vigot, P. Carninci, C. Plessy, T. Launey P14 The evolution of imperfection and imperfection of evolution: the functional and functionless fractions of the human genome D. Graur P16 Species-independent identification of known and novel recurrent genomic entities in multiple cancer patients J. Friis-Nielsen, J. M. Izarzugaza, S. Brunak P18 Discovery of active gene modules which are densely conserved across multiple cancer types reveal their prognostic power and mutually exclusive mutation patterns B. S. Soibam P19 Whole exome sequencing of dysplastic leukoplakia tissue indicates sequential accumulation of somatic mutations from oral precancer to cancer D. Das, N. Biswas, S. Das, S. Sarkar, A. Maitra, C. Panda, P. Majumder P21 Epigenetic mechanisms of carcinogensis by hereditary breast cancer genes J. J. Gruber, N. Jaeger, M. Snyder P22 RNA direct: a novel RNA enrichment strategy applied to transcripts associated with solid tumors K. Patel, S. Bowman, T. Davis, D. Kraushaar, A. Emerman, S. Russello, N. Henig, C. Hendrickson P23 RNA sequencing identifies gene mutations for neuroblastoma K. Zhang P24 Participation of SFRP1 in the modulation of TMPRSS2-ERG fusion gene in prostate cancer cell lines M. Rodriguez-Dorantes, C. D. Cruz-Hernandez, C. D. P. Garcia-Tobilla, S. Solorzano-Rosales P25 Targeted Methylation Sequencing of Prostate Cancer N. Jäger, J. Chen, R. Haile, M. Hitchins, J. D. Brooks, M. Snyder P26 Mutant TPMT alleles in children with acute lymphoblastic leukemia from México City and Yucatán, Mexico S. Jiménez-Morales, M. Ramírez, J. Nuñez, V. Bekker, Y. Leal, E. Jiménez, A. Medina, A. Hidalgo, J. Mejía P28 Genetic modifiers of Alström syndrome J. Naggert, G. B. Collin, K. DeMauro, R. Hanusek, P. M. Nishina P31 Association of genomic variants with the occurrence of angiotensin-converting-enzyme inhibitor (ACEI)-induced coughing among Filipinos E. M. Cutiongco De La Paz, R. Sy, J. Nevado, P. Reganit, L. Santos, J. D. Magno, F. E. Punzalan , D. Ona , E. Llanes, R. L. Santos-Cortes , R. Tiongco, J. Aherrera, L. Abrahan, P. Pagauitan-Alan; Philippine Cardiogenomics Study Group P32 The use of “humanized” mouse models to validate disease association of a de novo GARS variant and to test a novel gene therapy strategy for Charcot-Marie-Tooth disease type 2D K. H. Morelli, J. S. Domire, N. Pyne, S. Harper, R. Burgess P34 Molecular regulation of chondrogenic human induced pluripotent stem cells M. A. Gari, A. Dallol, H. Alsehli, A. Gari, M. Gari, A. Abuzenadah P35 Molecular profiling of hematologic malignancies: implementation of a variant assessment algorithm for next generation sequencing data analysis and clinical reporting M. Thomas, M. Sukhai, S. Garg, M. Misyura, T. Zhang, A. Schuh, T. Stockley, S. Kamel-Reid P36 Accessing genomic evidence for clinical variants at NCBI S. Sherry, C. Xiao, D. Slotta, K. Rodarmer, M. Feolo, M. Kimelman, G. Godynskiy, C. O’Sullivan, E. Yaschenko P37 NGS-SWIFT: a cloud-based variant analysis framework using control-accessed sequencing data from DBGAP/SRA C. Xiao, E. Yaschenko, S. Sherry P38 Computational assessment of drug induced hepatotoxicity through gene expression profiling C. Rangel-Escareño, H. Rueda-Zarate P40 Flowr: robust and efficient pipelines using a simple language-agnostic approach;ultraseq; fast modular pipeline for somatic variation calling using flowr S. Seth, S. Amin, X. Song, X. Mao, H. Sun, R. G. Verhaak, A. Futreal, J. Zhang P41 Applying “Big data” technologies to the rapid analysis of heterogenous large cohort data S. J. Whiite, T. Chiang, A. English, J. Farek, Z. Kahn, W. Salerno, N. Veeraraghavan, E. Boerwinkle, R. Gibbs P42 FANTOM5 web resource for the large-scale genome-wide transcription start site activity profiles of wide-range of mammalian cells T. Kasukawa, M. Lizio, J. Harshbarger, S. Hisashi, J. Severin, A. Imad, S. Sahin, T. C. Freeman, K. Baillie, A. Sandelin, P. Carninci, A. R. R. Forrest, H. Kawaji, The FANTOM Consortium P43 Rapid and scalable typing of structural variants for disease cohorts W. Salerno, A. English, S. N. Shekar, A. Mangubat, J. Bruestle, E. Boerwinkle, R. A. Gibbs P44 Polymorphism of glutathione S-transferases and sulphotransferases genes in an Arab population A. H. Salem, M. Ali, A. Ibrahim, M. Ibrahim P46 Genetic divergence of CYP3A5*3 pharmacogenomic marker for native and admixed Mexican populations J. C. Fernandez-Lopez, V. Bonifaz-Peña, C. Rangel-Escareño, A. Hidalgo-Miranda, A. V. Contreras P47 Whole exome sequence meta-analysis of 13 white blood cell, red blood cell, and platelet traits L. Polfus, CHARGE and NHLBI Exome Sequence Project Working Groups P48 Association of adipoq gene with type 2 diabetes and related phenotypes in african american men and women: The jackson heart study S. Davis, R. Xu, S. Gebeab, P Riestra, A Gaye, R. Khan, J. Wilson, A. Bidulescu P49 Common variants in casr gene are associated with serum calcium levels in koreans S. H. Jung, N. Vinayagamoorthy, S. H. Yim, Y. J. Chung P50 Inference of multiple-wave population admixture by modeling decay of linkage disequilibrium with multiple exponential functions Y. Zhou, S. Xu P51 A Bayesian framework for generalized linear mixed models in genome-wide association studies X. Wang, V. Philip, G. Carter P52 Targeted sequencing approach for the identification of the genetic causes of hereditary hearing impairment A. A. Abuzenadah, M. Gari, R. Turki, A. Dallol P53 Identification of enhancer sequences by ATAC-seq open chromatin profiling A. Uyar, A. Kaygun, S. Zaman, E. Marquez, J. George, D. Ucar P54 Direct enrichment for the rapid preparation of targeted NGS libraries C. L. Hendrickson, A. Emerman, D. Kraushaar, S. Bowman, N. Henig, T. Davis, S. Russello, K. Patel P56 Performance of the Agilent D5000 and High Sensitivity D5000 ScreenTape assays for the Agilent 4200 Tapestation System R. Nitsche, L. Prieto-Lafuente P57 ClinVar: a multi-source archive for variant interpretation M. Landrum, J. Lee, W. Rubinstein, D. Maglott P59 Association of functional variants and protein physical interactions of human MUTY homolog linked with familial adenomatous polyposis and colorectal cancer syndrome Z. Abduljaleel, W. Khan, F. A. Al-Allaf, M. Athar , M. M. Taher, N. Shahzad P60 Modification of the microbiom constitution in the gut using chicken IgY antibodies resulted in a reduction of acute graft-versus-host disease after experimental bone marrow transplantation A. Bouazzaoui, E. Huber, A. Dan, F. A. Al-Allaf, W. Herr, G. Sprotte, J. Köstler, A. Hiergeist, A. Gessner, R. Andreesen, E. Holler P61 Compound heterozygous mutation in the LDLRgene in Saudi patients suffering severe hypercholesterolemia F. Al-Allaf, A. Alashwal, Z. Abduljaleel, M. Taher, A. Bouazzaoui, H. Abalkhail, A. Al-Allaf, R. Bamardadh, M. Athar
Published: 2016
Full Text: View/download PDF

23. A new method for maintaining semi-structured data described in XML.

Author: Kasukawa, T., Matsuda, H., Nakanishi, M., and Hashimoto, A.
Published: 1999
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24. Gamma loop dysfunction of the quadriceps femoris of elderly patients hospitalized after fall injury.

Author: Konishi Y, Kasukawa T, Tobita H, Nishino A, and Konishi M
Published: 2007

25. Human genome meeting 2016

Author: Srivastava, A. K., Wang, Y., Huang, R., Skinner, C., Thompson, T., Pollard, L., Wood, T., Luo, F., Stevenson, R., Polimanti, R., Gelernter, J., Lin, X., Lim, I. Y., Wu, Y., Teh, A. L., Chen, L., Aris, I. M., Soh, S. E., Tint, M. T., MacIsaac, J. L., Yap, F., Kwek, K., Saw, S. M., Kobor, M. S., Meaney, M. J., Godfrey, K. M., Chong, Y. S., Holbrook, J. D., Lee, Y. S., Gluckman, P. D., Karnani, N., Kapoor, A., Lee, D., Chakravarti, A., Maercker, C., Graf, F., Boutros, M., Stamoulis, G., Santoni, F., Makrythanasis, P., Letourneau, A., Guipponi, M., Panousis, N., Garieri, M., Ribaux, P., Falconnet, E., Borel, C., Antonarakis, S. E., Kumar, S., Curran, J., Blangero, J., Chatterjee, S., Akiyama, J., Auer, D., Berrios, C., Pennacchio, L., Donti, T. R., Cappuccio, G., Miller, M., Atwal, P., Kennedy, A., Cardon, A., Bacino, C., Emrick, L., Hertecant, J., Baumer, F., Porter, B., Bainbridge, M., Bonnen, P., Graham, B., Sutton, R., Sun, Q., Elsea, S., Hu, Z., Wang, P., Zhu, Y., Zhao, J., Xiong, M., Bennett, David A., Hidalgo-Miranda, A., Romero-Cordoba, S., Rodriguez-Cuevas, S., Rebollar-Vega, R., Tagliabue, E., Iorio, M., D’Ippolito, E., Baroni, S., Kaczkowski, B., Tanaka, Y., Kawaji, H., Sandelin, A., Andersson, R., Itoh, M., Lassmann, T., Hayashizaki, Y., Carninci, P., Forrest, A. R. R., Semple, C. A., Rosenthal, E. A., Shirts, B., Amendola, L., Gallego, C., Horike-Pyne, M., Burt, A., Robertson, P., Beyers, P., Nefcy, C., Veenstra, D., Hisama, F., Bennett, R., Dorschner, M., Nickerson, D., Smith, J., Patterson, K., Crosslin, D., Nassir, R., Zubair, N., Harrison, T., Peters, U., Jarvik, G., Menghi, F., Inaki, K., Woo, X., Kumar, P., Grzeda, K., Malhotra, A., Kim, H., Ucar, D., Shreckengast, P., Karuturi, K., Keck, J., Chuang, J., Liu, E. T., Ji, B., Tyler, A., Ananda, G., Carter, G., Nikbakht, H., Montagne, M., Zeinieh, M., Harutyunyan, A., Mcconechy, M., Jabado, N., Lavigne, P., Majewski, J., Goldstein, J. B., Overman, M., Varadhachary, G., Shroff, R., Wolff, R., Javle, M., Futreal, A., Fogelman, D., Bravo, L., Fajardo, W., Gomez, H., Castaneda, C., Rolfo, C., Pinto, J. A., Akdemir, K. C., Chin, L., Patterson, S., Statz, C., Mockus, S., Nikolaev, S. N., Bonilla, X. I., Parmentier, L., King, B., Bezrukov, F., Kaya, G., Zoete, V., Seplyarskiy, V., Sharpe, H., McKee, T., Popadin, K., Basset-Seguin, N., Chaabene, R. Ben, Andrianova, M., Verdan, C., Grosdemange, K., Sumara, O., Eilers, M., Aifantis, I., Michielin, O., de Sauvage, F., Antonarakis, S., Likhitrattanapisal, S., Lincoln, S., Kurian, A., Desmond, A., Yang, S., Kobayashi, Y., Ford, J., Ellisen, L., Peters, T. L., Alvarez, K. R., Hollingsworth, E. F., Lopez-Terrada, D. H., Hastie, A., Dzakula, Z., Pang, A. W., Lam, E. T., Anantharaman, T., Saghbini, M., Cao, H., Gonzaga-Jauregui, C., Ma, L., King, A., Rosenzweig, E. Berman, Krishnan, U., Reid, J. G., Overton, J. D., Dewey, F., Chung, W. K., Small, K., DeLuca, A., Cremers, F., Lewis, R. A., Puech, V., Bakall, B., Silva-Garcia, R., Rohrschneider, K., Leys, M., Shaya, F. S., Stone, E., Sobreira, N. L., Schiettecatte, F., Ling, H., Pugh, E., Witmer, D., Hetrick, K., Zhang, P., Doheny, K., Valle, D., Hamosh, A., Jhangiani, S. N., Akdemir, Z. Coban, Bainbridge, M. N., Charng, W., Wiszniewski, W., Gambin, T., Karaca, E., Bayram, Y., Eldomery, M. K., Posey, J., Doddapaneni, H., Hu, J., Sutton, V. R., Muzny, D. M., Boerwinkle, E. A., Lupski, J. R., Gibbs, R. A., Shekar, S., Salerno, W., English, A., Mangubat, A., Bruestle, J., Thorogood, A., Knoppers, B. M., Takahashi, H., Nitta, K. R., Kozhuharova, A., Suzuki, A. M., Sharma, H., Cotella, D., Santoro, C., Zucchelli, S., Gustincich, S., Mulvihill, J. J., Baynam, G., Gahl, W., Groft, S. C., Kosaki, K., Lasko, P., Melegh, B., Taruscio, D., Ghosh, R., Plon, S., Scherer, S., Qin, X., Sanghvi, R., Walker, K., Chiang, T., Muzny, D., Wang, L., Black, J., Boerwinkle, E., Weinshilboum, R., Gibbs, R., Karpinets, T., Calderone, T., Wani, K., Yu, X., Creasy, C., Haymaker, C., Forget, M., Nanda, V., Roszik, J., Wargo, J., Haydu, L., Song, X., Lazar, A., Gershenwald, J., Davies, M., Bernatchez, C., Zhang, J., Woodman, S., Chesler, E. J., Reynolds, T., Bubier, J. A., Phillips, C., Langston, M. A., Baker, E. J., Lin, N., Amos, C., Calhoun, V., Dobretsberger, O., Egger, M., Leimgruber, F., Sadedin, S., Oshlack, A., Antonio, V. A. A., Ono, N., Ahmed, Z., Bolisetty, M., Zeeshan, S., Anguiano, E., Sarkar, A., Nandineni, M. R., Zeng, C., Shao, J., Liang, T., Pham, K., Chee-Wei, Y., Dongsheng, L., Lai-Ping, W., Lian, D., Hee, R. O. Twee, Yunus, Y., Aghakhanian, F., Mokhtar, S. S., Lok-Yung, C. V., Bhak, J., Phipps, M., Shuhua, X., Yik-Ying, T., Kumar, V., Boon-Peng, H., Campbell, I., Young, M. -A., James, P., Rain, M., Mohammad, G., Kukreti, R., Pasha, Q., Akilzhanova, A. R., Guelly, C., Abilova, Z., Rakhimova, S., Akhmetova, A., Kairov, U., Trajanoski, S., Zhumadilov, Z., Bekbossynova, M., Schumacher, C., Sandhu, S., Harkins, T., Makarov, V., Glenn, R., Momin, Z., Dilrukshi, B., Chao, H., Meng, Q., Gudenkauf, B., Kshitij, R., Jayaseelan, J., Nessner, C., Lee, S., Blankenberg, K., Lewis, L., Han, Y., Dinh, H., Jireh, S., Buhay, C., Liu, X., Wang, Q., Ding, Y., Veeraraghavan, N., Yang, Y., Beaudet, A. L., Eng, C. M., Worley, K. C. C., Liu, Y., Hughes, D. S. T., Murali, S. C., Harris, R. A., English, A. C., Hampton, O. A., Larsen, P., Beck, C., Wang, M., Kovar, C. L., Salerno, W. J., Yoder, A., Richards, S., Rogers, J., Raveenedran, M., Xue, C., Dahdouli, M., Cox, L., Fan, G., Ferguson, B., Hovarth, J., Johnson, Z., Kanthaswamy, S., Kubisch, M., Platt, M., Smith, D., Vallender, E., Wiseman, R., Below, J., Yu, F., Lin, J., Zhang, Y., Ouyang, Z., Moore, A., Wang, Z., Hofmann, J., Purdue, M., Stolzenberg-Solomon, R., Weinstein, S., Albanes, D., Liu, C. S., Cheng, W. L., Lin, T. T., Lan, Q., Rothman, N., Berndt, S., Chen, E. S., Bahrami, H., Khoshzaban, A., Keshal, S. Heidari, Alharbi, K. K. R., Zhalbinova, M., Akilzhanova, A., Bekbosynova, M., Myrzakhmetova, S., Matar, M., Mili, N., Molinari, R., Ma, Y., Guerrier, S., Elhawary, N., Tayeb, M., Bogari, N., Qotb, N., McClymont, S. A., Hook, P. W., Goff, L. A., McCallion, A., Kong, Y., Charette, J. R., Hicks, W. L., Naggert, J. K., Zhao, L., Nishina, P. M., Edrees, B. M., Athar, M., Al-Allaf, F. A., Taher, M. M., Khan, W., Bouazzaoui, A., Harbi, N. A., Safar, R., Al-Edressi, H., Anazi, A., Altayeb, N., Ahmed, M. A., Alansary, K., Abduljaleel, Z., Kratz, A., Beguin, P., Poulain, S., Kaneko, M., Takahiko, C., Matsunaga, A., Kato, S., Bertin, N., Vigot, R., Plessy, C., Launey, T., Graur, D., Friis-Nielsen, J., Izarzugaza, J. M., Brunak, S., Chakraborty, A., Basak, J., Mukhopadhyay, A., Soibam, B. S., Das, D., Biswas, N., Das, S., Sarkar, S., Maitra, A., Panda, C., Majumder, P., Morsy, H., Gaballah, A., Samir, M., Shamseya, M., Mahrous, H., Ghazal, A., Arafat, W., Hashish, M., Gruber, J. J., Jaeger, N., Snyder, M., Patel, K., Bowman, S., Davis, T., Kraushaar, D., Emerman, A., Russello, S., Henig, N., Hendrickson, C., Zhang, K., Rodriguez-Dorantes, M., Cruz-Hernandez, C. D., Garcia-Tobilla, C. D. P., Solorzano-Rosales, S., Jäger, N., Chen, J., Haile, R., Hitchins, M., Brooks, J. D., Jiménez-Morales, S., Ramírez, M., Nuñez, J., Bekker, V., Leal, Y., Jiménez, E., Medina, A., Hidalgo, A., Mejía, J., Halytskiy, V., Naggert, J., Collin, G. B., DeMauro, K., Hanusek, R., Belhassa, K., Belhassan, K., Bouguenouch, L., Samri, I., Sayel, H., moufid, FZ., El Bouchikhi, I., Trhanint, S., Hamdaoui, H., Elotmani, I., Khtiri, I., Kettani, O., Quibibo, L., Ahagoud, M., Abbassi, M., Ouldim, K., Marusin, A. V., Kornetov, A. N., Swarovskaya, M., Vagaiceva, K., Stepanov, V., De La Paz, E. M. Cutiongco, Sy, R., Nevado, J., Reganit, P., Santos, L., Magno, J. D., Punzalan, F. E., Ona, D., Llanes, E., Santos-Cortes, R. L., Tiongco, R., Aherrera, J., Abrahan, L., Pagauitan-Alan, P., Morelli, K. H., Domire, J. S., Pyne, N., Harper, S., Burgess, R., Gari, M. A., Dallol, A., Alsehli, H., Gari, A., Gari, M., Abuzenadah, A., Thomas, M., Sukhai, M., Garg, S., Misyura, M., Zhang, T., Schuh, A., Stockley, T., Kamel-Reid, S., Sherry, S., Xiao, C., Slotta, D., Rodarmer, K., Feolo, M., Kimelman, M., Godynskiy, G., O’Sullivan, C., Yaschenko, E., Rangel-Escareño, C., Rueda-Zarate, H., Tayubi, I. A., Mohammed, R., Ahmed, I., Ahmed, T., Seth, S., Amin, S., Mao, X., Sun, H., Verhaak, R. G., Whiite, S. J., Farek, J., Kahn, Z., Kasukawa, T., Lizio, M., Harshbarger, J., Hisashi, S., Severin, J., Imad, A., Sahin, S., Freeman, T. C., Baillie, K., Shekar, S. N., Salem, A. H., Ali, M., Ibrahim, A., Ibrahim, M., Barrera, H. A., Garza, L., Torres, J. A., Barajas, V., Ulloa-Aguirre, A., Kershenobich, D., Mortaji, Shahroj, Guizar, Pedro, Loera, Eliezer, Moreno, Karen, De León, Adriana, Monsiváis, Daniela, Gómez, Jackeline, Cardiel, Raquel, Fernandez-Lopez, J. C., Bonifaz-Peña, V., Contreras, A. V., Polfus, L., Wang, X., Philip, V., Abuzenadah, A. A., Turki, R., Uyar, A., Kaygun, A., Zaman, S., Marquez, E., George, J., Hendrickson, C. L., Starr, D. B., Baird, M., Kirkpatrick, B., Sheets, K., Nitsche, R., Prieto-Lafuente, L., Landrum, M., Lee, J., Rubinstein, W., Maglott, D., Thavanati, P. K. R., de Dios, A. Escoto, Hernandez, R. E. Navarro, Aldrate, M. E. Aguilar, Mejia, M. R. Ruiz, Kanala, K. R. R., Shahzad, N., Huber, E., Dan, A., Herr, W., Sprotte, G., Köstler, J., Hiergeist, A., Gessner, A., Andreesen, R., Holler, E., Al-Allaf, F., Alashwal, A., Taher, M., Abalkhail, H., Al-Allaf, A., Bamardadh, R., Filiptsova, O., Kobets, M., Kobets, Y., Burlaka, I., Timoshyna, I., Kobets, M. N., Al-allaf, F. A., Mohiuddin, M. T., Zainularifeen, A., Mohammed, A., and Owaidah, T.
Full Text: View/download PDF

26. The transcriptional landscape of the mammalian genome

Author: Carninci, P., Kasukawa, T., and Katayama, S.

27. FREP: A database of functional repeats in mouse cDNAs

Author: Nagashima, T., Matsuda, H., Silva, D. G., Nikolai Petrovsky, Kasukawa, T., Arakawa, T., Carninci, P., Kawai, J., Hayashizaki, Y., Konagaya, A., and Schönbach, C.

28. MaXML: mouse annotation XML

Author: Kasukawa, T., Hidemasa Bono, Hayashizaki, Y., Okazaki, Y., and Matsuda, H.

29. Systematic analysis of transcription start sites in avian development

Author: Lizio M., Deviatiiarov R., Nagai H., Galan L., Arner E., Itoh M., Lassmann T., Kasukawa T., Hasegawa A., Ros M., Hayashizaki Y., Carninci P., Forrest A., Kawaji H., Gusev O., Sheng G., Lizio M., Deviatiiarov R., Nagai H., Galan L., Arner E., Itoh M., Lassmann T., Kasukawa T., Hasegawa A., Ros M., Hayashizaki Y., Carninci P., Forrest A., Kawaji H., Gusev O., and Sheng G.
Abstract: © 2017 Lizio et al. Cap Analysis of Gene Expression (CAGE) in combination with single-molecule sequencing technology allows precision mapping of transcription start sites (TSSs) and genome-wide capture of promoter activities in differentiated and steady state cell populations. Much less is known about whether TSS profiling can characterize diverse and non-steady state cell populations, such as the approximately 400 transitory and heterogeneous cell types that arise during ontogeny of vertebrate animals. To gain such insight, we used the chick model and performed CAGE-based TSS analysis on embryonic samples covering the full 3-week developmental period. In total, 31,863 robust TSS peaks ( > 1 tag per million [TPM]) were mapped to the latest chicken genome assembly, of which 34% to 46% were active in any given developmental stage. ZENBU, a web-based, open-source platform, was used for interactive data exploration. TSSs of genes critical for lineage differentiation could be precisely mapped and their activities tracked throughout development, suggesting that non-steady state and heterogeneous cell populations are amenable to CAGE-based transcriptional analysis. Our study also uncovered a large set of extremely stable housekeeping TSSs and many novel stage-specific ones. We furthermore demonstrated that TSS mapping could expedite motif-based promoter analysis for regulatory modules associated with stage-specific and housekeeping genes. Finally, using Brachyury as an example, we provide evidence that precise TSS mapping in combination with Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)-on technology enables us, for the first time, to efficiently target endogenous avian genes for transcriptional activation. Taken together, our results represent the first report of genome-wide TSS mapping in birds and the first systematic developmental TSS analysis in any amniote species (birds and mammals). By facilitating promoter-based molecular analysis and genetic m

30. An integrated expression atlas of miRNAs and their promoters in human and mouse

Author: De Rie D., Abugessaisa I., Alam T., Arner E., Arner P., Ashoor H., Åström G., Babina M., Bertin N., Burroughs A., Carlisle A., Daub C., Detmar M., Deviatiiarov R., Fort A., Gebhard C., Goldowitz D., Guhl S., Ha T., Harshbarger J., Hasegawa A., Hashimoto K., Herlyn M., Heutink P., Hitchens K., Hon C., Huang E., Ishizu Y., Kai C., Kasukawa T., Klinken P., Lassmann T., Lecellier C., Lee W., Lizio M., Makeev V., Mathelier A., Medvedeva Y., Mejhert N., Mungall C., Noma S., Ohshima M., Okada-Hatakeyama M., Persson H., Rizzu P., Roudnicky F., Sætrom P., Sato H., Severin J., Shin J., Swoboda R., Tarui H., Toyoda H., Vitting-Seerup K., Winteringham L., Yamaguchi Y., Yasuzawa K., Yoneda M., Yumoto N., Zabierowski S., Zhang P., Wells C., Summers K., Kawaji H., Sandelin A., Rehli M., Hayashizaki Y., De Rie D., Abugessaisa I., Alam T., Arner E., Arner P., Ashoor H., Åström G., Babina M., Bertin N., Burroughs A., Carlisle A., Daub C., Detmar M., Deviatiiarov R., Fort A., Gebhard C., Goldowitz D., Guhl S., Ha T., Harshbarger J., Hasegawa A., Hashimoto K., Herlyn M., Heutink P., Hitchens K., Hon C., Huang E., Ishizu Y., Kai C., Kasukawa T., Klinken P., Lassmann T., Lecellier C., Lee W., Lizio M., Makeev V., Mathelier A., Medvedeva Y., Mejhert N., Mungall C., Noma S., Ohshima M., Okada-Hatakeyama M., Persson H., Rizzu P., Roudnicky F., Sætrom P., Sato H., Severin J., Shin J., Swoboda R., Tarui H., Toyoda H., Vitting-Seerup K., Winteringham L., Yamaguchi Y., Yasuzawa K., Yoneda M., Yumoto N., Zabierowski S., Zhang P., Wells C., Summers K., Kawaji H., Sandelin A., Rehli M., and Hayashizaki Y.
Abstract: © 2017 Nature America, Inc., part of Springer Nature. MicroRNAs (miRNAs) are short non-coding RNAs with key roles in cellular regulation. As part of the fifth edition of the Functional Annotation of Mammalian Genome (FANTOM5) project, we created an integrated expression atlas of miRNAs and their promoters by deep-sequencing 492 short RNA (sRNA) libraries, with matching Cap Analysis Gene Expression (CAGE) data, from 396 human and 47 mouse RNA samples. Promoters were identified for 1,357 human and 804 mouse miRNAs and showed strong sequence conservation between species. We also found that primary and mature miRNA expression levels were correlated, allowing us to use the primary miRNA measurements as a proxy for mature miRNA levels in a total of 1,829 human and 1,029 mouse CAGE libraries. We thus provide a broad atlas of miRNA expression and promoters in primary mammalian cells, establishing a foundation for detailed analysis of miRNA expression patterns and transcriptional control regions.

31. Systematic analysis of transcription start sites in avian development

Author: Lizio M., Deviatiiarov R., Nagai H., Galan L., Arner E., Itoh M., Lassmann T., Kasukawa T., Hasegawa A., Ros M., Hayashizaki Y., Carninci P., Forrest A., Kawaji H., Gusev O., Sheng G., Lizio M., Deviatiiarov R., Nagai H., Galan L., Arner E., Itoh M., Lassmann T., Kasukawa T., Hasegawa A., Ros M., Hayashizaki Y., Carninci P., Forrest A., Kawaji H., Gusev O., and Sheng G.
Abstract: © 2017 Lizio et al. Cap Analysis of Gene Expression (CAGE) in combination with single-molecule sequencing technology allows precision mapping of transcription start sites (TSSs) and genome-wide capture of promoter activities in differentiated and steady state cell populations. Much less is known about whether TSS profiling can characterize diverse and non-steady state cell populations, such as the approximately 400 transitory and heterogeneous cell types that arise during ontogeny of vertebrate animals. To gain such insight, we used the chick model and performed CAGE-based TSS analysis on embryonic samples covering the full 3-week developmental period. In total, 31,863 robust TSS peaks ( > 1 tag per million [TPM]) were mapped to the latest chicken genome assembly, of which 34% to 46% were active in any given developmental stage. ZENBU, a web-based, open-source platform, was used for interactive data exploration. TSSs of genes critical for lineage differentiation could be precisely mapped and their activities tracked throughout development, suggesting that non-steady state and heterogeneous cell populations are amenable to CAGE-based transcriptional analysis. Our study also uncovered a large set of extremely stable housekeeping TSSs and many novel stage-specific ones. We furthermore demonstrated that TSS mapping could expedite motif-based promoter analysis for regulatory modules associated with stage-specific and housekeeping genes. Finally, using Brachyury as an example, we provide evidence that precise TSS mapping in combination with Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)-on technology enables us, for the first time, to efficiently target endogenous avian genes for transcriptional activation. Taken together, our results represent the first report of genome-wide TSS mapping in birds and the first systematic developmental TSS analysis in any amniote species (birds and mammals). By facilitating promoter-based molecular analysis and genetic m

32. An integrated expression atlas of miRNAs and their promoters in human and mouse

Author: De Rie D., Abugessaisa I., Alam T., Arner E., Arner P., Ashoor H., Åström G., Babina M., Bertin N., Burroughs A., Carlisle A., Daub C., Detmar M., Deviatiiarov R., Fort A., Gebhard C., Goldowitz D., Guhl S., Ha T., Harshbarger J., Hasegawa A., Hashimoto K., Herlyn M., Heutink P., Hitchens K., Hon C., Huang E., Ishizu Y., Kai C., Kasukawa T., Klinken P., Lassmann T., Lecellier C., Lee W., Lizio M., Makeev V., Mathelier A., Medvedeva Y., Mejhert N., Mungall C., Noma S., Ohshima M., Okada-Hatakeyama M., Persson H., Rizzu P., Roudnicky F., Sætrom P., Sato H., Severin J., Shin J., Swoboda R., Tarui H., Toyoda H., Vitting-Seerup K., Winteringham L., Yamaguchi Y., Yasuzawa K., Yoneda M., Yumoto N., Zabierowski S., Zhang P., Wells C., Summers K., Kawaji H., Sandelin A., Rehli M., Hayashizaki Y., De Rie D., Abugessaisa I., Alam T., Arner E., Arner P., Ashoor H., Åström G., Babina M., Bertin N., Burroughs A., Carlisle A., Daub C., Detmar M., Deviatiiarov R., Fort A., Gebhard C., Goldowitz D., Guhl S., Ha T., Harshbarger J., Hasegawa A., Hashimoto K., Herlyn M., Heutink P., Hitchens K., Hon C., Huang E., Ishizu Y., Kai C., Kasukawa T., Klinken P., Lassmann T., Lecellier C., Lee W., Lizio M., Makeev V., Mathelier A., Medvedeva Y., Mejhert N., Mungall C., Noma S., Ohshima M., Okada-Hatakeyama M., Persson H., Rizzu P., Roudnicky F., Sætrom P., Sato H., Severin J., Shin J., Swoboda R., Tarui H., Toyoda H., Vitting-Seerup K., Winteringham L., Yamaguchi Y., Yasuzawa K., Yoneda M., Yumoto N., Zabierowski S., Zhang P., Wells C., Summers K., Kawaji H., Sandelin A., Rehli M., and Hayashizaki Y.
Abstract: © 2017 Nature America, Inc., part of Springer Nature. MicroRNAs (miRNAs) are short non-coding RNAs with key roles in cellular regulation. As part of the fifth edition of the Functional Annotation of Mammalian Genome (FANTOM5) project, we created an integrated expression atlas of miRNAs and their promoters by deep-sequencing 492 short RNA (sRNA) libraries, with matching Cap Analysis Gene Expression (CAGE) data, from 396 human and 47 mouse RNA samples. Promoters were identified for 1,357 human and 804 mouse miRNAs and showed strong sequence conservation between species. We also found that primary and mature miRNA expression levels were correlated, allowing us to use the primary miRNA measurements as a proxy for mature miRNA levels in a total of 1,829 human and 1,029 mouse CAGE libraries. We thus provide a broad atlas of miRNA expression and promoters in primary mammalian cells, establishing a foundation for detailed analysis of miRNA expression patterns and transcriptional control regions.

33. 4. Carcinoma of the Rectum in Young Generation

Author: Onoda, H., primary, Katoh, Y., additional, Kobayashi, K., additional, Kasukawa, T., additional, and Yoshio, T., additional
Published: 1975
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34. IV. Study of Ten Year Survival Rates and New Staging of the 325 patients with Rectoanal Carcinoma

Author: Kasukawa, T., primary
Published: 1979
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35. I. Two Cases of Anal Carcinoma Associated with Fistula

Author: Fukasawa, H., primary, Kasukawa, T., additional, Kamata, S., additional, Osaku, T., additional, Ando, H., additional, Ichimori, S., additional, and Akima, M., additional
Published: 1978
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36. 1. The Clinicopathology of Early Cancer and the Modificated Classification (Staging) of Cancer of the Colon and Rectum

Author: Kasukawa, T., primary
Published: 1973
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37. Clinicopathology of the Ano-Rectal Cancer

Author: Kasukawa, T., primary
Published: 1973
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38. Automatic identification of small molecules that promote cell conversion and reprogramming

Author: Antonella Iuliano, Akira Hasegawa, Xin Gao, Patrizia Annunziata, Davide Cacchiarelli, Diego di Bernardo, Erik Arner, Francesco Napolitano, Diego L. Medina, Sara Napolitano, Takeya Kasukawa, Melissa Cardon, Lorenzo Vaccaro, Luca Giorgio Wanderlingh, Trisevgeni Rapakoulia, Napolitano, F., Rapakoulia, T., Annunziata, P., Hasegawa, A., Cardon, M., Napolitano, S., Vaccaro, L., Iuliano, A., Wanderlingh, L. G., Kasukawa, T., Medina Sanabria Diego, Luis., Cacchiarelli, D., Gao, X., di Bernardo, D., and Arner, E.
Subjects: 0301 basic medicine, Resource, Cell type, In silico, Induced Pluripotent Stem Cells, Cell, cell conversion, Context (language use), Computational biology, Cell fate determination, Biology, Biochemistry, Regenerative medicine, Small Molecule Libraries, Automation, Mice, 03 medical and health sciences, 0302 clinical medicine, Genetics, medicine, Animals, Cluster Analysis, 030304 developmental biology, 0303 health sciences, bioinformatic, Drug discovery, Transdifferentiation, Reproducibility of Results, reprogramming, Cell Biology, bioinformatics, Cellular Reprogramming, Small molecule, 3. Good health, small molecules, 030104 developmental biology, medicine.anatomical_structure, 030220 oncology & carcinogenesis, Reprogramming, 030217 neurology & neurosurgery, Algorithms, Developmental Biology
Abstract: Summary Controlling cell fate has great potential for regenerative medicine, drug discovery, and basic research. Although transcription factors are able to promote cell reprogramming and transdifferentiation, methods based on their upregulation often show low efficiency. Small molecules that can facilitate conversion between cell types can ameliorate this problem working through safe, rapid, and reversible mechanisms. Here, we present DECCODE, an unbiased computational method for identification of such molecules based on transcriptional data. DECCODE matches a large collection of drug-induced profiles for drug treatments against a large dataset of primary cell transcriptional profiles to identify drugs that either alone or in combination enhance cell reprogramming and cell conversion. Extensive validation in the context of human induced pluripotent stem cells shows that DECCODE is able to prioritize drugs and drug combinations enhancing cell reprogramming. We also provide predictions for cell conversion with single drugs and drug combinations for 145 different cell types., Graphical abstract, Highlights • DECCODE method for identification of drugs that promote cell conversion • Predicts drugs that alone or in combination increase reprogramming efficiency • Validated for reprogramming of human fibroblast to hiPSCs • Treatment suggestions provided for 145 target cell types, In this article, Napolitano, Rapakoulia, and colleagues present DECCODE, a method for automatic identification of drugs that alone or in combination promote cell conversion and reprogramming. They validate the method for reprogramming of human fibroblasts to induced pluripotent stem cells (hiPSCs), and provide predicted treatments for conversion to 145 target cell types.
Published: 2020
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39. Update of the FANTOM web resource: enhancement for studying noncoding genomes.

Author: Nobusada T, Yip CW, Agrawal S, Severin J, Abugessaisa I, Hasegawa A, Hon CC, Ide S, Koido M, Kondo A, Masuya H, Oki S, Tagami M, Takada T, Terao C, Thalhath N, Walker S, Yasuzawa K, Shin JW, de Hoon MJL, Carninci P, Kawaji H, and Kasukawa T
Subjects: Humans, Animals, Genome genetics, Databases, Genetic, Regulatory Elements, Transcriptional, Genomics methods, Induced Pluripotent Stem Cells metabolism, Software, Molecular Sequence Annotation, Internet, RNA, Long Noncoding genetics, RNA, Long Noncoding metabolism
Abstract: The FANTOM web resource (https://fantom.gsc.riken.jp/) has been a unique resource for studying mammalian genomes, which is built on the research activities conducted in the international collaborative project FANTOM (Functional ANnoTation Of the Mammalian genome). In recent updates, we expanded annotations for long non-coding RNAs (lncRNAs) and transcribed cis-regulatory elements (CREs). The former was derived from the large-scale lncRNA perturbations in induced pluripotent stem cells (iPSCs) and integrative analysis of Hi-C data conducted in the sixth iteration of the project (FANTOM6). The resulting annotations of lncRNAs, according to the impact on cellular and molecular phenotypes and the potential RNA-chromatin interactions, are accessible via the interactive ZENBU-Reports framework. The latter involves a new platform, fanta.bio (https://fanta.bio/), which collects transcribed CREs identified via use of an extended dataset of CAGE profiles. The CREs, with their annotations including genetic and epigenetic information, are accessible via a dedicated interface as well as the UCSC Genome Browser Database. These updates offer enhanced opportunities to investigate the functions of non-coding regions within mammalian genomes., (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)
Published: 2025
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40. Successful Diagnosis of Sengers Syndrome Using a Comprehensive Genomic Analysis.

Author: Nakamura K, Yatsuka Y, Naito S, Hasegawa A, Kasukawa T, Kondo A, Kishita Y, Sugiyama Y, Onuki T, Ebihara T, Tsuruoka T, Fushimi T, Ohtake A, Murayama K, Imai-Okazaki A, and Okazaki Y
Subjects: Humans, Male, Female, Cardiomyopathy, Hypertrophic genetics, Cardiomyopathy, Hypertrophic diagnosis, Muscular Diseases genetics, Muscular Diseases diagnosis, Whole Genome Sequencing methods, Acidosis, Lactic genetics, Acidosis, Lactic diagnosis, Genetic Testing methods, Genetic Testing standards, Cardiomyopathies, Cataract genetics, Cataract diagnosis, Phosphotransferases (Alcohol Group Acceptor) genetics
Abstract: Background: Sengers syndrome is an autosomal recessive mitochondrial DNA depletion syndrome characterized by hypertrophic cardiomyopathy, congenital cataracts, skeletal myopathy, exercise intolerance, and lactic acidosis. Dysfunction of acylglycerol kinase (AGK) is responsible for the disease, and several AGK gene variants have been reported., Methods: We employed a comprehensive genomic analysis approach, including whole-genome sequencing and RNA sequencing, combined with various bioinformatics tools., Results: Our analysis successfully diagnosed Sengers syndrome in a patient by detecting a known pathogenic variant and a previously unreported large deletion involving the AGK gene in a segmental duplication., Conclusion: This study demonstrates the effectiveness of combining multiple genomic analysis approaches for the accurate diagnosis of Sengers syndrome, particularly in cases involving complex genetic variations such as large deletions in segmental duplications., (© 2024 The Author(s). Molecular Genetics & Genomic Medicine published by Wiley Periodicals LLC.)
Published: 2025
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41. Widespread 3'UTR capped RNAs derive from G-rich regions in proximity to AGO2 binding sites.

Author: Haberman N, Digby H, Faraway R, Cheung R, Chakrabarti AM, Jobbins AM, Parr C, Yasuzawa K, Kasukawa T, Yip CW, Kato M, Takahashi H, Carninci P, Vernia S, Ule J, Sibley CR, Martinez-Sanchez A, and Lenhard B
Subjects: Binding Sites, Humans, RNA Caps metabolism, RNA, Messenger metabolism, RNA, Messenger genetics, HeLa Cells, 3' Untranslated Regions genetics, Argonaute Proteins metabolism, Argonaute Proteins genetics
Abstract: The 3' untranslated region (3'UTR) plays a crucial role in determining mRNA stability, localisation, translation and degradation. Cap analysis of gene expression (CAGE), a method for the detection of capped 5' ends of mRNAs, additionally reveals a large number of apparently 5' capped RNAs derived from locations within the body of the transcript, including 3'UTRs. Here, we provide direct evidence that these 3'UTR-derived RNAs are indeed capped and widespread in mammalian cells. By using a combination of AGO2 enhanced individual nucleotide resolution UV crosslinking and immunoprecipitation (eiCLIP) and CAGE following siRNA treatment, we find that these 3'UTR-derived RNAs likely originate from AGO2-binding sites, and most often occur at locations with G-rich motifs bound by the RNA-binding protein UPF1. High-resolution imaging and long-read sequencing analysis validate several 3'UTR-derived RNAs, showcase their variable abundance and show that they may not co-localise with the parental mRNAs. Taken together, we provide new insights into the origin and prevalence of 3'UTR-derived RNAs, show the utility of CAGE-seq for their genome-wide detection and provide a rich dataset for exploring new biology of a poorly understood new class of RNAs., (© 2024. The Author(s).)
Published: 2024
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42. Efficacy of exercise with the hybrid assistive limb lumbar type on physical function in mobility-limited older adults: A 5-week randomized controlled trial.

Author: Saito Y, Nakamura S, Kasukawa T, Nagasawa M, Oguma Y, and Narimatsu H
Subjects: Aged, Female, Humans, Male, Activities of Daily Living, Frail Elderly, Frailty physiopathology, Frailty rehabilitation, Independent Living, Muscle Strength physiology, Single-Blind Method, Treatment Outcome, Walking Speed, Exercise Therapy methods, Mobility Limitation, Sarcopenia physiopathology, Sarcopenia rehabilitation
Abstract: Background: Sarcopenia and frailty often worsen in older adults because of declines in activities of daily living and social connections that are associated with chronic diseases and traumatic injuries such as falls and fractures. Exercise intervention for sarcopenia can take >3 months to improve muscle mass, muscle strength, and walking speed. Thus, a specialized intervention system for shorter periods of time is needed. In this study, we aimed to evaluate the short-term efficacy of an exercise program using the wearable cyborg Hybrid Assistive Limb (HAL) lumbar type in physical function in mobility-limited older adults who do not require transition to long-term care., Methods: This randomized, single-blind, parallel-group study involved 79 community-dwelling older adults with physical frailty or locomotive syndrome assigned to an intervention group (n = 40) with the HAL lumbar type exercise program or a control group (n = 39) without the exercise program. The intervention group underwent trunk training (including trunk and hip flexion, standing and sitting from a single sitting position, and squats) and gait training (treadmill and parallel bars) twice a week for 5 weeks while wearing the HAL lumbar type. The 10-m usual and maximum walking speeds, Timed Up and Go test results, 5-times chair-standing test results, 5-question Geriatric Locomotive Function Scale (GLFS-5) scores, body-fat percentage, and muscle mass were measured before and after the intervention and analyzed using the intention-to-treat method., Results: The intervention (23 % male; mean age, 74.7 ± 4.7 years) and control (21 % male; mean age, 75.1 ± 4.1 years) groups did not differ significantly in baseline characteristics. Seventy-seven participants completed the program; two withdrew for personal reasons. The mean difference (standard error) between the groups for the primary outcome (usual walking speed) was 0.35 (0.04) m/s; the time-by-group interaction was significant (p < 0.001). Secondary outcomes (maximum walking speed, Timed Up and Go test results, 5-times chair-standing test results, and GLFS-5 scores) significantly improved in the intervention group. Body composition was unchanged in both groups., Conclusions: A 5-week exercise program using the HAL lumbar type is a promising option for community-dwelling older adults with limited mobility who do not require nursing care, resulting in clinically meaningful improvements in most physical functions within a short period., Competing Interests: Declaration of competing interest None., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)
Published: 2024
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43. Annotation of nuclear lncRNAs based on chromatin interactions.

Author: Agrawal S, Buyan A, Severin J, Koido M, Alam T, Abugessaisa I, Chang HY, Dostie J, Itoh M, Kere J, Kondo N, Li Y, Makeev VJ, Mendez M, Okazaki Y, Ramilowski JA, Sigorskikh AI, Strug LJ, Yagi K, Yasuzawa K, Yip CW, Hon CC, Hoffman MM, Terao C, Kulakovskiy IV, Kasukawa T, Shin JW, Carninci P, and de Hoon MJL
Subjects: Humans, Molecular Sequence Annotation, Cell Nucleus metabolism, Cell Nucleus genetics, Genome, Human, Promoter Regions, Genetic, RNA, Long Noncoding genetics, RNA, Long Noncoding metabolism, Chromatin metabolism, Chromatin genetics
Abstract: The human genome is pervasively transcribed and produces a wide variety of long non-coding RNAs (lncRNAs), constituting the majority of transcripts across human cell types. Some specific nuclear lncRNAs have been shown to be important regulatory components acting locally. As RNA-chromatin interaction and Hi-C chromatin conformation data showed that chromatin interactions of nuclear lncRNAs are determined by the local chromatin 3D conformation, we used Hi-C data to identify potential target genes of lncRNAs. RNA-protein interaction data suggested that nuclear lncRNAs act as scaffolds to recruit regulatory proteins to target promoters and enhancers. Nuclear lncRNAs may therefore play a role in directing regulatory factors to locations spatially close to the lncRNA gene. We provide the analysis results through an interactive visualization web portal at https://fantom.gsc.riken.jp/zenbu/reports/#F6_3D_lncRNA., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Agrawal 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: 2024
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44. OVCH1 Antisense RNA 1 is differentially expressed between non-frail and frail old adults.

Author: Abugessaisa I, Manabe RI, Kawashima T, Tagami M, Takahashi C, Okazaki Y, Bandinelli S, Kasukawa T, and Ferrucci L
Subjects: Humans, Male, Female, Aged, Frail Elderly, Gene Expression Profiling, RNA, Antisense genetics, Frailty genetics, RNA, Long Noncoding genetics
Abstract: While some old adults stay healthy and non-frail up to late in life, others experience multimorbidity and frailty often accompanied by a pro-inflammatory state. The underlying molecular mechanisms for those differences are still obscure. Here, we used gene expression analysis to understand the molecular underpinning between non-frail and frail individuals in old age. Twenty-four adults (50% non-frail and 50% frail) from InCHIANTI study were included. Total RNA extracted from whole blood was analyzed by Cap Analysis of Gene Expression (CAGE). CAGE identified transcription start site (TSS) and active enhancer regions. We identified a set of differentially expressed (DE) TSS and enhancer between non-frail and frail and male and female participants. Several DE TSSs were annotated as lncRNA (XIST and TTTY14) and antisense RNAs (ZFX-AS1 and OVCH1 Antisense RNA 1). The promoter region chr6:366,786,54-366,787,97;+ was DE and overlapping the longevity CDKN1A gene. GWAS-LD enrichment analysis identifies overlapping LD-blocks with the DE regions with reported traits in GWAS catalog (isovolumetric relaxation time and urinary tract infection frequency). Furthermore, we used weighted gene co-expression network analysis (WGCNA) to identify changes of gene expression associated with clinical traits and identify key gene modules. We performed functional enrichment analysis of the gene modules with significant trait/module correlation. One gene module is showing a very distinct pattern in hub genes. Glycogen Phosphorylase L (PYGL) was the top ranked hub gene between non-frail and frail. We predicted transcription factor binding sites (TFBS) and motif activity. TF involved in age-related pathways (e.g., FOXO3 and MYC) shows different expression patterns between non-frail and frail participants. Expanding the study of OVCH1 Antisense RNA 1 and PYGL may help understand the mechanisms leading to loss of homeostasis that ultimately causes frailty., (© 2023. The Author(s).)
Published: 2024
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45. ROR2 expression predicts human induced pluripotent stem cell differentiation into neural stem/progenitor cells and GABAergic neurons.

Author: Kuroda T, Yasuda S, Matsuyama S, Miura T, Sawada R, Matsuyama A, Yamamoto Y, Morioka MS, Kawaji H, Kasukawa T, Itoh M, Akutsu H, Kawai J, and Sato Y
Subjects: Humans, Cell Differentiation genetics, Cell Line, Commerce, GABAergic Neurons, Receptor Tyrosine Kinase-like Orphan Receptors genetics, Induced Pluripotent Stem Cells
Abstract: Despite the development of various in vitro differentiation protocols for the efficient derivation of specific cell types, human induced pluripotent stem cell (hiPSC) lines have varing ability to differentiate into specific lineages. Therefore, surrogate markers for accurately predicting the differentiation propensity of hiPSC lines may facilitate cell-based therapeutic product development and manufacture. We attempted to identify marker genes that could predict the differentiation propensity of hiPSCs into neural stem/progenitor cells (NS/PCs). Using Spearman's rank correlation coefficients, we investigated genes in the undifferentiated state, the expression levels of which were significantly correlated with the neuronal differentiation propensity of several hiPSC lines. Among genes significantly correlated with NS/PC differentiation (P < 0.01), we identified ROR2 as a novel predictive marker. ROR2 expression in hiPSCs was negatively correlated with NS/PC differentiation tendency, regardless of the differentiation method, whereas its knockdown enhanced differentiation. ROR2 regulates NS/PC differentiation, suggesting that ROR2 is functionally essential for NS/PC differentiation. Selecting cell lines with relatively low ROR2 expression facilitated identification of hiPSCs that can differentiate into NS/PCs. Cells with ROR2 knockdown showed increased efficiency of differentiation into forebrain GABAergic neurons compared to controls. These findings suggest that ROR2 is a surrogate marker for selecting hiPSC lines appropriate for NS/PC and GABAergic neuronal differentiations., (© 2024. The Author(s).)
Published: 2024
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46. Single-Cell RNA-Seq Reveals LRRC75A-Expressing Cell Population Involved in VEGF Secretion of Multipotent Mesenchymal Stromal/Stem Cells Under Ischemia.

Author: Miura T, Kouno T, Takano M, Kuroda T, Yamamoto Y, Kusakawa S, Morioka MS, Sugawara T, Hirai T, Yasuda S, Sawada R, Matsuyama S, Kawaji H, Kasukawa T, Itoh M, Matsuyama A, Shin JW, Umezawa A, Kawai J, and Sato Y
Subjects: Humans, Bone Marrow Cells, Cell Differentiation, Cell Proliferation, Ischemia genetics, Ischemia therapy, Ischemia metabolism, Single-Cell Gene Expression Analysis, Stem Cells, Vascular Endothelial Growth Factors metabolism, Vascular Endothelial Growth Factors pharmacology, Mesenchymal Stem Cells, Vascular Endothelial Growth Factor A genetics, Vascular Endothelial Growth Factor A metabolism
Abstract: Human multipotent mesenchymal stromal/stem cells (MSCs) have been utilized in cell therapy for various diseases and their clinical applications are expected to increase in the future. However, the variation in MSC-based product quality due to the MSC heterogeneity has resulted in significant constraints in the clinical utility of MSCs. Therefore, we hypothesized that it might be important to identify and ensure/enrich suitable cell subpopulations for therapies using MSC-based products. In this study, we aimed to identify functional cell subpopulations to predict the efficacy of angiogenic therapy using bone marrow-derived MSCs (BM-MSCs). To assess its angiogenic potency, we observed various levels of vascular endothelial growth factor (VEGF) secretion among 11 donor-derived BM-MSC lines under in vitro ischemic culture conditions. Next, by clarifying the heterogeneity of BM-MSCs using single-cell RNA-sequencing analysis, we identified a functional cell subpopulation that contributed to the overall VEGF production in BM-MSC lines under ischemic conditions. We also found that leucine-rich repeat-containing 75A (LRRC75A) was more highly expressed in this cell subpopulation than in the others. Importantly, knockdown of LRRC75A using small interfering RNA resulted in significant inhibition of VEGF secretion in ischemic BM-MSCs, indicating that LRRC75A regulates VEGF secretion under ischemic conditions. Therefore, LRRC75A may be a useful biomarker to identify cell subpopulations that contribute to the angiogenic effects of BM-MSCs. Our work provides evidence that a strategy based on single-cell transcriptome profiles is effective for identifying functional cell subpopulations in heterogeneous MSC-based products., (© The Author(s) 2023. Published by Oxford University Press.)
Published: 2023
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47. Computational approach to evaluate scRNA-seq data quality and gene body coverage with SkewC.

Author: Abugessaisa I, Hasegawa A, Katayama S, Kere J, and Kasukawa T
Subjects: Sequence Analysis, RNA methods, Single-Cell Gene Expression Analysis, Single-Cell Analysis methods, Gene Expression Profiling methods, Data Accuracy
Abstract: SkewC is a single-cell RNA sequencing (scRNA-seq) data quality evaluation tool. The approach is based on determining gene body coverage, and its skewness, as a quality metric for each individual cell. SkewC distinguishes between two types of single cells: typical cells with prototypical gene body coverage profiles and skewed cells with skewed gene body coverage profiles. SkewC can be used on any scRNA-seq data as it is independent from the underlying technology used to generate the data. For complete details on the use and execution of this protocol, please refer to Abugessaisa et al. (2022). 1 ., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)
Published: 2023
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48. Antisense-oligonucleotide-mediated perturbation of long non-coding RNA reveals functional features in stem cells and across cell types.

Author: Yip CW, Hon CC, Yasuzawa K, Sivaraman DM, Ramilowski JA, Shibayama Y, Agrawal S, Prabhu AV, Parr C, Severin J, Lan YJ, Dostie J, Petri A, Nishiyori-Sueki H, Tagami M, Itoh M, López-Redondo F, Kouno T, Chang JC, Luginbühl J, Kato M, Murata M, Yip WH, Shu X, Abugessaisa I, Hasegawa A, Suzuki H, Kauppinen S, Yagi K, Okazaki Y, Kasukawa T, de Hoon M, Carninci P, and Shin JW
Subjects: Humans, Oligonucleotides, Antisense, Gene Expression Profiling methods, Embryonic Stem Cells metabolism, RNA, Long Noncoding genetics, RNA, Long Noncoding metabolism, Induced Pluripotent Stem Cells metabolism
Abstract: Within the scope of the FANTOM6 consortium, we perform a large-scale knockdown of 200 long non-coding RNAs (lncRNAs) in human induced pluripotent stem cells (iPSCs) and systematically characterize their roles in self-renewal and pluripotency. We find 36 lncRNAs (18%) exhibiting cell growth inhibition. From the knockdown of 123 lncRNAs with transcriptome profiling, 36 lncRNAs (29.3%) show molecular phenotypes. Integrating the molecular phenotypes with chromatin-interaction assays further reveals cis- and trans-interacting partners as potential primary targets. Additionally, cell-type enrichment analysis identifies lncRNAs associated with pluripotency, while the knockdown of LINC02595, CATG00000090305.1, and RP11-148B6.2 modulates colony formation of iPSCs. We compare our results with previously published fibroblasts phenotyping data and find that 2.9% of the lncRNAs exhibit a consistent cell growth phenotype, whereas we observe 58.3% agreement in molecular phenotypes. This highlights that molecular phenotyping is more comprehensive in revealing affected pathways., Competing Interests: Declaration of interests The authors declare that there is no conflict of interest., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)
Published: 2022
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49. Author Correction: IκBα is required for full transcriptional induction of some NFκB-regulated genes in response to TNF in MCF-7 cells.

Author: Ando M, Magi S, Seki M, Suzuki Y, Kasukawa T, Lefaudeux D, Hoffmann A, and Okada M
Published: 2022
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50. Systematic Functional Annotation Workflow for Insects.

Author: Bono H, Sakamoto T, Kasukawa T, and Tabunoki H
Abstract: Next-generation sequencing has revolutionized entomological study, rendering it possible to analyze the genomes and transcriptomes of non-model insects. However, use of this technology is often limited to obtaining the nucleotide sequences of target or related genes, with many of the acquired sequences remaining unused because other available sequences are not sufficiently annotated. To address this issue, we have developed a functional annotation workflow for transcriptome-sequenced insects to determine transcript descriptions, which represents a significant improvement over the previous method (functional annotation pipeline for insects). The developed workflow attempts to annotate not only the protein sequences obtained from transcriptome analysis but also the ncRNA sequences obtained simultaneously. In addition, the workflow integrates the expression-level information obtained from transcriptome sequencing for application as functional annotation information. Using the workflow, functional annotation was performed on the sequences obtained from transcriptome sequencing of the stick insect ( Entoria okinawaensis ) and silkworm ( Bombyx mori ), yielding richer functional annotation information than that obtained in our previous study. The improved workflow allows the more comprehensive exploitation of transcriptome data and is applicable to other insects because the workflow has been openly developed on GitHub.
Published: 2022
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