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3. 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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13. Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease

Author

Bergmann, S, Baillie, JK, Bretherick, A, Haley, CS, Clohisey, S, Grays, A, Neyton, LPA, Barrett, J, Stahl, EA, Tenesa, A, Andersson, R, Brown, JB, Faulkner, GJ, Lizio, M, Schaefer, U, Daub, C, Itoh, M, Kondo, N, Lassmann, T, Kawai, J, Mole, D, Bajic, VB, Heutink, P, Rehli, M, Kawaji, H, Sandelin, A, Suzuki, H, Satsangi, J, Wells, CA, Hacohen, N, Freeman, TC, Hayashizaki, Y, Carninci, P, Forrest, ARR, Hume, DA, Bergmann, S, Baillie, JK, Bretherick, A, Haley, CS, Clohisey, S, Grays, A, Neyton, LPA, Barrett, J, Stahl, EA, Tenesa, A, Andersson, R, Brown, JB, Faulkner, GJ, Lizio, M, Schaefer, U, Daub, C, Itoh, M, Kondo, N, Lassmann, T, Kawai, J, Mole, D, Bajic, VB, Heutink, P, Rehli, M, Kawaji, H, Sandelin, A, Suzuki, H, Satsangi, J, Wells, CA, Hacohen, N, Freeman, TC, Hayashizaki, Y, Carninci, P, Forrest, ARR, and Hume, DA

Abstract

Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn's disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits.

Published
2018

14. 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

15. Integrated Analysis of Epigenetic and Genetic Changes During MDS Progression Reveals the Tight Association of Epigenetic Changes with Genetic Selection

Author

Pohl, S., primary, Heudobler, D., additional, Loyola, V. Bengt Pastor, additional, Gebhard, C., additional, Mossner, M., additional, Jann, J.C., additional, Hirabayashi, S., additional, Nowak, D., additional, Wlodarski, M., additional, Hofmann, W.K., additional, Niemeyer, C., additional, and Rehli, M., additional

Published
2017
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16. The Constrained Maximal Expression Level Owing to Haploidy Shapes Gene Content on the Mammalian X Chromosome

Author

Hurst, LD, Ghanbarian, AT, Forrest, ARR, Huminiecki, L, Rehli, M, Kenneth Baillie, J, de Hoon, MJL, Haberle, V, Lassmann, T, Kulakovskiy, IV, Lizio, M, Itoh, M, Andersson, R, Mungall, CJ, Meehan, TF, Schmeier, S, Bertin, N, Jørgensen, M, Dimont, E, Arner, E, Schmidl, C, Schaefer, U, Medvedeva, YA, Plessy, C, Vitezic, M, Severin, J, Semple, CA, Ishizu, Y, Young, RS, Francescatto, M, Alam, I, Albanese, D, Altschuler, GM, Arakawa, T, Archer, JAC, Arner, P, Babina, M, Baker, S, Balwierz, PJ, Beckhouse, AG, Pradhan, SB, Blake, JA, Blumenthal, A, Bodega, B, Bonetti, A, Briggs, J, Brombacher, F, Maxwell Burroughs, A, Califano, A, Cannistraci, CV, Carbajo, D, Chen, Y, Chierici, M, Ciani, Y, Clevers, HC, Dalla, E, Davis, CA, Detmar, M, Diehl, AD, Dohi, T, Drabløs, F, Edge, ASB, Edinger, M, Ekwall, K, Endoh, M, Enomoto, H, Fagiolini, M, Fairbairn, L, and Fang, H

Abstract

© 2015 Hurst et al. X chromosomes are unusual in many regards, not least of which is their nonrandom gene content. The causes of this bias are commonly discussed in the context of sexual antagonism and the avoidance of activity in the male germline. Here, we examine the notion that, at least in some taxa, functionally biased gene content may more profoundly be shaped by limits imposed on gene expression owing to haploid expression of the X chromosome. Notably, if the X, as in primates, is transcribed at rates comparable to the ancestral rate (per promoter) prior to the X chromosome formation, then the X is not a tolerable environment for genes with very high maximal net levels of expression, owing to transcriptional traffic jams. We test this hypothesis using The Encyclopedia of DNA Elements (ENCODE) and data from the Functional Annotation of the Mammalian Genome (FANTOM5) project. As predicted, the maximal expression of human X-linked genes is much lower than that of genes on autosomes: on average, maximal expression is three times lower on the X chromosome than on autosomes. Similarly, autosome-to-X retroposition events are associated with lower maximal expression of retrogenes on the X than seen for X-to-autosome retrogenes on autosomes. Also as expected, X-linked genes have a lesser degree of increase in gene expression than autosomal ones (compared to the human/Chimpanzee common ancestor) if highly expressed, but not if lowly expressed. The traffic jam model also explains the known lower breadth of expression for genes on the X (and the Z of birds), as genes with broad expression are, on average, those with high maximal expression. As then further predicted, highly expressed tissue-specific genes are also rare on the X and broadly expressed genes on the X tend to be lowly expressed, both indicating that the trend is shaped by the maximal expression level not the breadth of expression per se. Importantly, a limit to the maximal expression level explains biased tissue of expression profiles of X-linked genes. Tissues whose tissue-specific genes are very highly expressed (e.g., secretory tissues, tissues abundant in structural proteins) are also tissues in which gene expression is relatively rare on the X chromosome. These trends cannot be fully accounted for in terms of alternative models of biased expression. In conclusion, the notion that it is hard for genes on the Therian X to be highly expressed, owing to transcriptional traffic jams, provides a simple yet robustly supported rationale of many peculiar features of X’s gene content, gene expression, and evolution.

Published
2015
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17. Analysis of the human monocyte-derived macrophage transcriptome and response to lipopolysaccharide provides new insights into genetic aetiology of inflammatory bowel disease

Author

Cho, JH, Baillie, JK, Arner, E, Daub, C, De Hoon, M, Itoh, M, Kawaji, H, Lassmann, T, Carninci, P, Forrest, ARR, Hayashizaki, Y, Consortium, F, Faulkner, GJ, Wells, CA, Rehli, M, Pavli, P, Summers, KM, Hume, DA, Cho, JH, Baillie, JK, Arner, E, Daub, C, De Hoon, M, Itoh, M, Kawaji, H, Lassmann, T, Carninci, P, Forrest, ARR, Hayashizaki, Y, Consortium, F, Faulkner, GJ, Wells, CA, Rehli, M, Pavli, P, Summers, KM, and Hume, DA

Abstract

The FANTOM5 consortium utilised cap analysis of gene expression (CAGE) to provide an unprecedented insight into transcriptional regulation in human cells and tissues. In the current study, we have used CAGE-based transcriptional profiling on an extended dense time course of the response of human monocyte-derived macrophages grown in macrophage colony-stimulating factor (CSF1) to bacterial lipopolysaccharide (LPS). We propose that this system provides a model for the differentiation and adaptation of monocytes entering the intestinal lamina propria. The response to LPS is shown to be a cascade of successive waves of transient gene expression extending over at least 48 hours, with hundreds of positive and negative regulatory loops. Promoter analysis using motif activity response analysis (MARA) identified some of the transcription factors likely to be responsible for the temporal profile of transcriptional activation. Each LPS-inducible locus was associated with multiple inducible enhancers, and in each case, transient eRNA transcription at multiple sites detected by CAGE preceded the appearance of promoter-associated transcripts. LPS-inducible long non-coding RNAs were commonly associated with clusters of inducible enhancers. We used these data to re-examine the hundreds of loci associated with susceptibility to inflammatory bowel disease (IBD) in genome-wide association studies. Loci associated with IBD were strongly and specifically (relative to rheumatoid arthritis and unrelated traits) enriched for promoters that were regulated in monocyte differentiation or activation. Amongst previously-identified IBD susceptibility loci, the vast majority contained at least one promoter that was regulated in CSF1-dependent monocyte-macrophage transitions and/or in response to LPS. On this basis, we concluded that IBD loci are strongly-enriched for monocyte-specific genes, and identified at least 134 additional candidate genes associated with IBD susceptibility from reanalysis

Published
2017

18. 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

19. 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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20. 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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22. [The 'classical' macrophage marker CD68 is strongly expressed in primary human fibroblasts]

Author

Leoni Kunz-Schughart, Weber A, Rehli M, Gottfried E, Brockhoff G, Sw, Krause, Andreesen R, and Kreutz M

Subjects
Antigens, CD, Cell Line, Tumor, Macrophages, Antigens, Differentiation, Myelomonocytic, Humans, RNA, RNA, Messenger, RNA, Neoplasm, Fibroblasts, Monocytes
Abstract

Monoclonal antibodies against the human homologue of mouse macrosialin, CD68, are generally commercialized as markers for human monocytes and macrophages. Indeed, CD68 is considered as a selective marker for human myeloid cells, although several previous immunohistochemical studies indicate that some antibody clones also react with other hematopoietic and non-hematopoietic cell types. The aim of our study was to verify these observations and to evaluate the reliability of CD68 as a macrophage marker.We investigated protein and RNA expression of CD68 in various fibroblast types and carcinoma cell lines as compared to monocytes and macrophages using immunohistochemistry, flow cytometry, and specific RT-PCR. Different monoclonal antibody clones against CD68 were applied including KP-1 and EBM11.As expected, the intensity of immunohistochemical and flow cytometric CD68 staining was dependent on both the antibody clone and the fixation procedure. However, fibroblasts isolated from normal skin, normal breast, breast tumor tissue, and osteoarthritis synovia clearly expressed CD68 protein at levels comparable to macrophages. The specificity of CD68 expression in fibroblasts was verified by RT-PCR which also showed some tumor cell types to express CD68 mRNA.Our findings clearly demonstrate that the expression of CD68 is not restricted to the macrophage lineage. This is highly relevant for experimental and diagnostic purposes, since anti CD68 antibodies cannot be accepted without reservations for the discrimination of myeloid cells and fibroblasts even in paraffin sections after formalin fixation.

Published
2006

25. Early epigenetic downregulation of WNK2 kinase during pancreatic ductal adenocarcinoma development

Author

Dutruel, C, primary, Bergmann, F, additional, Rooman, I, additional, Zucknick, M, additional, Weichenhan, D, additional, Geiselhart, L, additional, Kaffenberger, T, additional, Rachakonda, P S, additional, Bauer, A, additional, Giese, N, additional, Hong, C, additional, Xie, H, additional, Costello, J F, additional, Hoheisel, J, additional, Kumar, R, additional, Rehli, M, additional, Schirmacher, P, additional, Werner, J, additional, Plass, C, additional, Popanda, O, additional, and Schmezer, P, additional

Published
2013
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29. EVIDENCE THAT TREATMENT WITH DHRS9+ REGULATORY MACROPHAGES INDUCED BY FCγRIII LIGATION AND IFN-γ STIMULATION PROMOTES RENAL ALLOGRAFT TOLERANCE IN PATIENTS

Author

Hutchinson, J. A., primary, Riquelme, P., additional, Brown, D. P., additional, Sawitzki, B., additional, Rehli, M., additional, Tomiuk, S., additional, Schröder, J., additional, Sotnikova, A., additional, Miqueu, P., additional, Zuhayra, M., additional, Oberg, H. H., additional, Pascher, A., additional, Lützen, U., additional, Janen, U., additional, Thaiss, F., additional, Scheuermann, E., additional, Henze, E., additional, Chatenoud, L., additional, Volk, H., additional, Lechler, R. I., additional, Wood, K. J., additional, Kabelitz, D., additional, Schlitt, H. J., additional, Fändrich, F., additional, and Geissler, E. K., additional

Published
2010
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35. PU.1 and interferon consensus sequence-binding protein regulate the myeloid expression of the human Toll-like receptor 4 gene.

Author

Rehli, M, Poltorak, A, Schwarzfischer, L, Krause, S W, Andreesen, R, and Beutler, B

Abstract

The protein product of the Toll-like receptor (TLR) 4 gene has been implicated in the signal transduction events induced by lipopolysaccharide (LPS). In mice, destructive mutations of Tlr4 impede the normal response to LPS and cause a high susceptibility to Gram-negative infection. Expression of TLR4 mRNA in humans is restricted to a small number of cell types, including LPS-responsive myeloid cells, B-cells, and endothelial cells. To investigate the molecular basis for TLR4 expression in cells of myeloid origin, we cloned the human TLR4 gene and analyzed its putative 5'-proximal promoter. In transient transfections a region of only 75 base pairs upstream of the major transcription initiation site was sufficient to induce maximal luciferase activity in THP-1 cells. The sequence of this region is similar in human and mouse TLR4 genes and lacks a TATA box, typical Sp1-sites or CCAAT box sequences. Instead, it contains consensus-binding sites for Ets family transcription factors, octamer-binding factors, and a composite interferon response factor/Ets motif. The activity of the promoter in macrophages was strictly dependent on the integrity of both half sites of the composite interferon response factor/Ets motif, which was constitutively bound by the myeloid and B-cell-specific transcription factor PU.1 and interferon consensus sequence-binding protein. These results indicate that the two tissue-restricted transcription factors PU.1 and interferon consensus sequence-binding protein participate in the basal regulation of human TLR4 in myeloid cells. Cloning of the human TLR4 gene provides a basis for further investigation of the possible impact of genetic variations on the susceptibility to infection and sepsis.

Published
2000

37. Carboxypeptidase M is identical to the MAX.1 antigen and its expression is associated with monocyte to macrophage differentiation.

Author

Rehli, M, Krause, S W, Kreutz, M, and Andreesen, R

Abstract

The two monoclonal antibodies MAX.1 and MAX.11 recognize cell surface antigens that are almost undetectable on monocytes but highly expressed on differentiated macrophages. Biochemical characterization revealed that both antibodies detect the same 58-64-kDa glycoprotein anchored to the plasma membrane by glycosyl-phosphatidylinositol linkage. We purified the MAX.1/11 antigen by immunoaffinity chromatography using monoclonal antibody MAX.11. The NH2-terminal amino acid sequence was determined and turned out to be identical to the NH2-terminal sequence of the membrane-bound carboxypeptidase M. By precipitation with antibodies MAX.1 and MAX.11, membrane preparations of macrophages and placental microvilli were almost completely depleted of enzyme activity, indicating that the two antibodies indeed recognize carboxypeptidase M. Immunoreactivity of both antibodies correlates with the reported tissue distribution of enzyme activity. Expression of carboxypeptidase M on mRNA level and enzymatic activity markedly increase during in vitro differentiation of monocytes, according to the described increase in MAX.1 and MAX.11 antigen expression. Moreover, in vitro differentiated macrophages show the highest specific activity yet described in any tissue. In addition, carboxypeptidase M expression could be detected in HL-60, U937, and THP-1 myeloid cell lines. Vitamin D3-induced monocytic differentiation resulted in an increased carboxypeptidase M expression in all three cell lines. Further studies are needed to elucidate the functional role of carboxypeptidase M during monocytic differentiation and activation.

Published
1995

40. Identification of nonlymphoid-tissue regulatory T cell precursors

Author

Delacher, M., Imbusch, C., Hotz-Wagenblatt, A., Mallm, J. -P, Bauer, K., Riegel, D., Rendeiro, A., Bittner, S., Sanderink, L., Pant, A., Braband, K., Echtenachter, B., Hoffmann, P., Edinger, M., Bock, C., Rehli, M., Benedikt Brors, Schmidl, C., and Feuerer, M.

41. 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.

42. 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.

43. High frequency of functionally active Melan-A specific T cells in a patient with progressive immunoproteasome-deficient melanoma.

Author

Meidenbauer, N., Zippelius, A., Pittet, M. J., Laumer, M., Vogl, S., Heymann, J., Rehli, M., Seliger, B., Schwarz, S., Le Gal, F-A., Dietrich, P. Y., Andreesen, R., Romero, P., and Mackensen, A.

Subjects
T cells, LYMPHOCYTES, LEUCOCYTES, MELANOMA, METASTASIS, IMMUNE response, LYMPH nodes
Abstract

The article reports on an unexpected high frequency of Melan-A-specific cytotoxic T lymphocytes (CTL) in a melanoma patient with progressive lymph node metastases, consisting of 18 percent and 12.8 percent of total peripheral blood and tumor-infiltrating CD8+ T cells, respectively. It suggests that immunotherapeutic approaches should not only focus on the induction of a robust anti-tumor immune response, but also have to target tumor immune escape mechanisms.

Published
2004
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44. Intercellular nanotube-mediated mitochondrial transfer enhances T cell metabolic fitness and antitumor efficacy.

Author

Baldwin JG, Heuser-Loy C, Saha T, Schelker RC, Slavkovic-Lukic D, Strieder N, Hernandez-Lopez I, Rana N, Barden M, Mastrogiovanni F, Martín-Santos A, Raimondi A, Brohawn P, Higgs BW, Gebhard C, Kapoor V, Telford WG, Gautam S, Xydia M, Beckhove P, Frischholz S, Schober K, Kontarakis Z, Corn JE, Iannacone M, Inverso D, Rehli M, Fioravanti J, Sengupta S, and Gattinoni L

Subjects
Animals, Mice, Humans, Mesenchymal Stem Cells metabolism, Mesenchymal Stem Cells cytology, Cell Line, Tumor, Neoplasms therapy, Neoplasms metabolism, Neoplasms pathology, Neoplasms immunology, Female, Mitochondria metabolism, Mice, Inbred C57BL, Nanotubes chemistry, CD8-Positive T-Lymphocytes immunology, CD8-Positive T-Lymphocytes metabolism
Abstract

Mitochondrial loss and dysfunction drive T cell exhaustion, representing major barriers to successful T cell-based immunotherapies. Here, we describe an innovative platform to supply exogenous mitochondria to T cells, overcoming these limitations. We found that bone marrow stromal cells establish nanotubular connections with T cells and leverage these intercellular highways to transplant stromal cell mitochondria into CD8 + T cells. Optimal mitochondrial transfer required Talin 2 on both donor and recipient cells. CD8 + T cells with donated mitochondria displayed enhanced mitochondrial respiration and spare respiratory capacity. When transferred into tumor-bearing hosts, these supercharged T cells expanded more robustly, infiltrated the tumor more efficiently, and exhibited fewer signs of exhaustion compared with T cells that did not take up mitochondria. As a result, mitochondria-boosted CD8 + T cells mediated superior antitumor responses, prolonging animal survival. These findings establish intercellular mitochondrial transfer as a prototype of organelle medicine, opening avenues to next-generation cell therapies., Competing Interests: Declaration of interests J.G.B., T.S., J.F., S.S., and L.G. have a patent application for the use of mitochondrial transfer technology in cancer immunotherapies. P.B. and S.G. have an employee relationship and have stock in AstraZeneca. B.W.H. has an employee relationship and has stock in Genmab. L.G. has consulting agreements with Lyell Immunopharma, Instil Bio, and Advaxis. L.G. is on the scientific advisory board of Poseida Therapeutics and Kiromic and a stockholder of Poseida Therapeutics. M.I. participates in advisory boards/consultancies for Gilead Sciences, Third Rock Ventures, Antios Therapeutics, Asher Biotherapeutics, GentiBio, Clexio Biosciences, Sybilla, and BlueJay Therapeutics. J.F. has an employee relationship and has stock in Lyell Immunopharma. S.S. is a founder and owns equity in Vyome Therapeutics Inc. and Alyssum Therapeutics Inc., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Published
2024
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45. STAG2 mutations reshape the cohesin-structured spatial chromatin architecture to drive gene regulation in acute myeloid leukemia.

Author

Fischer A, Hernández-Rodríguez B, Mulet-Lazaro R, Nuetzel M, Hölzl F, van Herk S, Kavelaars FG, Stanewsky H, Ackermann U, Niang AH, Diaz N, Reuschel E, Strieder N, Hernández-López I, Valk PJM, Vaquerizas JM, Rehli M, Delwel R, and Gebhard C

Subjects
Humans, Hematopoietic Stem Cells metabolism, Cell Differentiation genetics, Gene Expression Regulation, Leukemic, Antigens, Nuclear metabolism, Antigens, Nuclear genetics, Nuclear Proteins, Cohesins, Leukemia, Myeloid, Acute genetics, Leukemia, Myeloid, Acute pathology, Leukemia, Myeloid, Acute metabolism, Cell Cycle Proteins metabolism, Cell Cycle Proteins genetics, Chromatin metabolism, Chromosomal Proteins, Non-Histone metabolism, Chromosomal Proteins, Non-Histone genetics, Mutation genetics
Abstract

Cohesin shapes the chromatin architecture, including enhancer-promoter interactions. Its components, especially STAG2, but not its paralog STAG1, are frequently mutated in myeloid malignancies. To elucidate the underlying mechanisms of leukemogenesis, we comprehensively characterized genetic, transcriptional, and chromatin conformational changes in acute myeloid leukemia (AML) patient samples. Specific loci displayed altered cohesin occupancy, gene expression, and local chromatin activation, which were not compensated by the remaining STAG1-cohesin. These changes could be linked to disrupted spatial chromatin looping in cohesin-mutated AMLs. Complementary depletion of STAG2 or STAG1 in primary human hematopoietic progenitors (HSPCs) revealed effects resembling STAG2-mutant AML-specific changes following STAG2 knockdown, not invoked by the depletion of STAG1. STAG2-deficient HSPCs displayed impaired differentiation capacity and maintained HSPC-like gene expression. This work establishes STAG2 as a key regulator of chromatin contacts, gene expression, and differentiation in the hematopoietic system and identifies candidate target genes that may be implicated in human leukemogenesis., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Published
2024
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46. Single-cell chromatin accessibility and transposable element landscapes reveal shared features of tissue-residing immune cells.

Author

Simon M, Stüve P, Schmidleithner L, Bittner S, Beumer N, Strieder N, Schmidl C, Pant A, Gebhard C, Eigenberger A, Rehli M, Prantl L, Hehlgans T, Brors B, Imbusch CD, Delacher M, and Feuerer M

Subjects
Animals, Mice, Organ Specificity genetics, Transcription Factors metabolism, Transcription Factors genetics, Mice, Inbred C57BL, Humans, Chromatin metabolism, Chromatin genetics, T-Lymphocytes, Regulatory immunology, DNA Transposable Elements genetics, Single-Cell Analysis
Abstract

Tissue adaptation is required for regulatory T (Treg) cell function within organs. Whether this program shares aspects with other tissue-localized immune populations is unclear. Here, we analyzed single-cell chromatin accessibility data, including the transposable element (TE) landscape of CD45 + immune cells from colon, skin, adipose tissue, and spleen. We identified features of organ-specific tissue adaptation across different immune cells. Focusing on tissue Treg cells, we found conservation of the Treg tissue adaptation program in other tissue-localized immune cells, such as amphiregulin-producing T helper (Th)17 cells. Accessible TEs can act as regulatory elements, but their contribution to tissue adaptation is not understood. TE landscape analysis revealed an enrichment of specific transcription factor binding motifs in TE regions within accessible chromatin peaks. TEs, specifically from the LTR family, were located in enhancer regions and associated with tissue adaptation. These findings broaden our understanding of immune tissue residency and provide an important step toward organ-specific immune interventions., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Published
2024
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47. LIM-domain-only 4 (LMO4) enhances CD8 + T-cell stemness and tumor rejection by boosting IL-21-STAT3 signaling.

Author

Schelker RC, Fioravanti J, Mastrogiovanni F, Baldwin JG, Rana N, Li P, Chen P, Vadász T, Spolski R, Heuser-Loy C, Slavkovic-Lukic D, Noronha P, Damiano G, Raccosta L, Maggioni D, Pullugula S, Lin JX, Oh J, Grandinetti P, Lecce M, Hesse L, Kocks E, Martín-Santos A, Gebhard C, Telford WG, Ji Y, Restifo NP, Russo V, Rehli M, Herr W, Leonard WJ, and Gattinoni L

Subjects
Mice, Animals, Humans, Interleukins genetics, Interleukins immunology, Cell Differentiation genetics, Cell Differentiation immunology, LIM Domain Proteins genetics, LIM Domain Proteins immunology, CD8-Positive T-Lymphocytes immunology, STAT3 Transcription Factor genetics, STAT3 Transcription Factor immunology, STAT3 Transcription Factor metabolism, Adaptor Proteins, Signal Transducing genetics, Adaptor Proteins, Signal Transducing immunology, Signal Transduction immunology, Signal Transduction genetics
Abstract

High frequencies of stem-like memory T cells in infusion products correlate with superior patient outcomes across multiple T cell therapy trials. Herein, we analyzed a published CRISPR activation screening to identify transcriptional regulators that could be harnessed to augment stem-like behavior in CD8 + T cells. Using IFN-γ production as a proxy for CD8 + T cell terminal differentiation, LMO4 emerged among the top hits inhibiting the development of effectors cells. Consistently, we found that Lmo4 was downregulated upon CD8 + T cell activation but maintained under culture conditions facilitating the formation of stem-like T cells. By employing a synthetic biology approach to ectopically express LMO4 in antitumor CD8 + T cells, we enabled selective expansion and enhanced persistence of transduced cells, while limiting their terminal differentiation and senescence. LMO4 overexpression promoted transcriptional programs regulating stemness, increasing the numbers of stem-like CD8 + memory T cells and enhancing their polyfunctionality and recall capacity. When tested in syngeneic and xenograft tumor models, LMO4 overexpression boosted CD8 + T cell antitumor immunity, resulting in enhanced tumor regression. Rather than directly modulating gene transcription, LMO4 bound to JAK1 and potentiated STAT3 signaling in response to IL-21, inducing the expression of target genes (Tcf7, Socs3, Junb, and Zfp36) crucial for memory responses. CRISPR/Cas9-deletion of Stat3 nullified the enhanced memory signature conferred by LMO4, thereby abrogating the therapeutic benefit of LMO4 overexpression. These results establish LMO4 overexpression as an effective strategy to boost CD8 + T cell stemness, providing a new synthetic biology tool to bolster the efficacy of T cell-based immunotherapies., (© 2024. The Author(s).)

Published
2024
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48. D-2-hydroxyglutarate supports a tolerogenic phenotype with lowered major histocompatibility class II expression in non-malignant dendritic cells and acute myeloid leukemia cells.

Author

Hammon K, Renner K, Althammer M, Voll F, Babl N, Decking SM, Siska PJ, Matos C, Conejo ZEC, Mendes K, Einwag F, Siegmund H, Iberl S, Berger RS, Dettmer K, Schoenmehl R, Brochhausen C, Herr W, Oefner PJ, Rehli M, Thomas S, and Kreutz M

Subjects
Humans, Mice, Animals, Phenotype, Cell Differentiation drug effects, Lactic Acid metabolism, Immune Tolerance drug effects, Isocitrate Dehydrogenase genetics, Leukemia, Myeloid, Acute drug therapy, Leukemia, Myeloid, Acute metabolism, Leukemia, Myeloid, Acute genetics, Leukemia, Myeloid, Acute immunology, Leukemia, Myeloid, Acute pathology, Dendritic Cells immunology, Dendritic Cells metabolism, Dendritic Cells drug effects, Glutarates metabolism, Glutarates pharmacology, Histocompatibility Antigens Class II genetics, Histocompatibility Antigens Class II metabolism
Abstract

D-2-hydroxyglutarate (D-2-HG) accumulates in patients with acute myeloid leukemia (AML) with mutated isocitrate dehydrogenase (IDH) and in other malignancies. D-2-HG suppresses antitumor T-cell immunity but little is known about potential effects on non-malignant myeloid cells. Here we show that D-2-HG impairs human but not murine dendritic cell differentiation, resulting in a tolerogenic phenotype with low major histocompatibility class II expression. In line with this, IDH-mutated AML blasts exhibited lower expression of HLA-DP and were less susceptible to lysis by HLA-DP-specific T cells. Interestingly, besides its expected impact on DNA demethylation, D-2-HG reprogrammed metabolism towards increased lactate production in dendritic cells and AML. Vitamin C accelerated DNA demethylation, but only the combination of vitamin C and glycolytic inhibition lowered lactate levels and supported major histocompatibility complex class II expression. Our results indicate an unexpected link between the immunosuppressive metabolites 2-HG and lactic acid and suggest a potentially novel therapeutic strategy with combinations of anti-glycolytic drugs and epigenetic modulators (hypomethylating agents) or other therapeutics for the treatment of AML.

Published
2024
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49. Oligoclonal CD4 + CXCR5 + T cells with a cytotoxic phenotype appear in tonsils and blood.

Author

Liang C, Spoerl S, Xiao Y, Habenicht KM, Haeusl SS, Sandner I, Winkler J, Strieder N, Eder R, Stanewsky H, Alexiou C, Dudziak D, Rosenwald A, Edinger M, Rehli M, Hoffmann P, Winkler TH, and Berberich-Siebelt F

Subjects
Humans, Phenotype, CD4-Positive T-Lymphocytes immunology, CD4-Positive T-Lymphocytes metabolism, Male, Female, Adult, Palatine Tonsil immunology, Palatine Tonsil metabolism, Palatine Tonsil cytology, Receptors, CXCR5 metabolism, Receptors, CXCR5 genetics
Abstract

In clinical situations, peripheral blood accessible CD3 + CD4 + CXCR5 + T-follicular helper (T FH ) cells may have to serve as a surrogate indicator for dysregulated germinal center responses in tissues. To determine the heterogeneity of T FH cells in peripheral blood versus tonsils, CD3 + CD4 + CD45RA - CXCR5 + cells of both origins were sorted. Transcriptomes, TCR repertoires and cell-surface protein expression were analysed by single-cell RNA sequencing, flow cytometry and immunohistochemistry. Reassuringly, all blood-circulating CD3 + CD4 + CXCR5 + T-cell subpopulations also appear in tonsils, there with some supplementary T FH characteristics, while peripheral blood-derived T FH cells display markers of proliferation and migration. Three further subsets of T FH cells, however, with bona fide T-follicular gene expression patterns, are exclusively found in tonsils. One additional, distinct and oligoclonal CD4 + CXCR5 + subpopulation presents pronounced cytotoxic properties. Those 'killer T FH (T FK ) cells' can be discovered in peripheral blood as well as among tonsillar cells but are located predominantly outside of germinal centers. They appear terminally differentiated and can be distinguished from all other T FH subsets by expression of NKG7 (TIA-1), granzymes, perforin, CCL5, CCR5, EOMES, CRTAM and CX3CR1. All in all, this study provides data for detailed CD4 + CXCR5 + T-cell assessment of clinically available blood samples and extrapolation possibilities to their tonsil counterparts., (© 2024. The Author(s).)

Published
2024
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50. Epigenetic alterations affecting hematopoietic regulatory networks as drivers of mixed myeloid/lymphoid leukemia.

Author

Mulet-Lazaro R, van Herk S, Nuetzel M, Sijs-Szabo A, Díaz N, Kelly K, Erpelinck-Verschueren C, Schwarzfischer-Pfeilschifter L, Stanewsky H, Ackermann U, Glatz D, Raithel J, Fischer A, Pohl S, Rijneveld A, Vaquerizas JM, Thiede C, Plass C, Wouters BJ, Delwel R, Rehli M, and Gebhard C

Subjects
Humans, CCAAT-Enhancer-Binding Proteins genetics, CCAAT-Enhancer-Binding Proteins metabolism, Lymphoid Enhancer-Binding Factor 1 genetics, Lymphoid Enhancer-Binding Factor 1 metabolism, CCCTC-Binding Factor metabolism, CCCTC-Binding Factor genetics, Gene Expression Regulation, Leukemic, Transcription Factors genetics, Transcription Factors metabolism, Chromatin metabolism, Chromatin genetics, Male, Precursor T-Cell Lymphoblastic Leukemia-Lymphoma genetics, Precursor T-Cell Lymphoblastic Leukemia-Lymphoma metabolism, Precursor T-Cell Lymphoblastic Leukemia-Lymphoma pathology, Female, Hematopoiesis genetics, Child, Transcriptome, Proto-Oncogene Proteins, Trans-Activators, Epigenesis, Genetic, DNA Methylation genetics, Gene Regulatory Networks, CpG Islands genetics
Abstract

Leukemias with ambiguous lineage comprise several loosely defined entities, often without a clear mechanistic basis. Here, we extensively profile the epigenome and transcriptome of a subgroup of such leukemias with CpG Island Methylator Phenotype. These leukemias exhibit comparable hybrid myeloid/lymphoid epigenetic landscapes, yet heterogeneous genetic alterations, suggesting they are defined by their shared epigenetic profile rather than common genetic lesions. Gene expression enrichment reveals similarity with early T-cell precursor acute lymphoblastic leukemia and a lymphoid progenitor cell of origin. In line with this, integration of differential DNA methylation and gene expression shows widespread silencing of myeloid transcription factors. Moreover, binding sites for hematopoietic transcription factors, including CEBPA, SPI1 and LEF1, are uniquely inaccessible in these leukemias. Hypermethylation also results in loss of CTCF binding, accompanied by changes in chromatin interactions involving key transcription factors. In conclusion, epigenetic dysregulation, and not genetic lesions, explains the mixed phenotype of this group of leukemias with ambiguous lineage. The data collected here constitute a useful and comprehensive epigenomic reference for subsequent studies of acute myeloid leukemias, T-cell acute lymphoblastic leukemias and mixed-phenotype leukemias., (© 2024. The Author(s).)

Published
2024
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