--- _id: '555' abstract: - lang: eng text: Conventional wisdom has it that proteins fold and assemble into definite structures, and that this defines their function. Glycosaminoglycans (GAGs) are different. In most cases the structures they form have a low degree of order, even when interacting with proteins. Here, we discuss how physical features common to all GAGs — hydrophilicity, charge, linearity and semi-flexibility — underpin the overall properties of GAG-rich matrices. By integrating soft matter physics concepts (e.g. polymer brushes and phase separation) with our molecular understanding of GAG–protein interactions, we can better comprehend how GAG-rich matrices assemble, what their properties are, and how they function. Taking perineuronal nets (PNNs) — a GAG-rich matrix enveloping neurons — as a relevant example, we propose that microphase separation determines the holey PNN anatomy that is pivotal to PNN functions. acknowledgement: "This work was supported by the European Research Council [Starting Grant 306435 ‘JELLY’; to RPR], the Spanish Ministry of Competitiveness and Innovation [MAT2014-54867-R, to RPR], the EPSRC Centre for Doctoral Training in Tissue Engineering and Regenerative Medicine — Innovation in Medical and Biological Engineering [EP/L014823/1, to JCFK], the Royal Society [RG160410, to JCFK], Wings for Life [WFL-UK-008/15, to JCFK] and the European Union, the Operational Programme Research, Development and Education in the framework of the project ‘Centre of Reconstructive Neuroscience’ [CZ.02.1.01/0.0./0.0/15_003/0000419, to JCFK]. AJD would like to thank Arthritis Research UK [16539, 19489] and the MRC [76445, G0900538] for funding his work on GAG–protein interactions.\r\n" article_processing_charge: No article_type: original author: - first_name: Ralf full_name: Richter, Ralf last_name: Richter - first_name: Natalia full_name: Baranova, Natalia id: 38661662-F248-11E8-B48F-1D18A9856A87 last_name: Baranova orcid: 0000-0002-3086-9124 - first_name: Anthony full_name: Day, Anthony last_name: Day - first_name: Jessica full_name: Kwok, Jessica last_name: Kwok citation: ama: 'Richter R, Baranova NS, Day A, Kwok J. Glycosaminoglycans in extracellular matrix organisation: Are concepts from soft matter physics key to understanding the formation of perineuronal nets? Current Opinion in Structural Biology. 2018;50:65-74. doi:10.1016/j.sbi.2017.12.002' apa: 'Richter, R., Baranova, N. S., Day, A., & Kwok, J. (2018). Glycosaminoglycans in extracellular matrix organisation: Are concepts from soft matter physics key to understanding the formation of perineuronal nets? Current Opinion in Structural Biology. Elsevier. https://doi.org/10.1016/j.sbi.2017.12.002' chicago: 'Richter, Ralf, Natalia S. Baranova, Anthony Day, and Jessica Kwok. “Glycosaminoglycans in Extracellular Matrix Organisation: Are Concepts from Soft Matter Physics Key to Understanding the Formation of Perineuronal Nets?” Current Opinion in Structural Biology. Elsevier, 2018. https://doi.org/10.1016/j.sbi.2017.12.002.' ieee: 'R. Richter, N. S. Baranova, A. Day, and J. Kwok, “Glycosaminoglycans in extracellular matrix organisation: Are concepts from soft matter physics key to understanding the formation of perineuronal nets?,” Current Opinion in Structural Biology, vol. 50. Elsevier, pp. 65–74, 2018.' ista: 'Richter R, Baranova NS, Day A, Kwok J. 2018. Glycosaminoglycans in extracellular matrix organisation: Are concepts from soft matter physics key to understanding the formation of perineuronal nets? Current Opinion in Structural Biology. 50, 65–74.' mla: 'Richter, Ralf, et al. “Glycosaminoglycans in Extracellular Matrix Organisation: Are Concepts from Soft Matter Physics Key to Understanding the Formation of Perineuronal Nets?” Current Opinion in Structural Biology, vol. 50, Elsevier, 2018, pp. 65–74, doi:10.1016/j.sbi.2017.12.002.' short: R. Richter, N.S. Baranova, A. Day, J. Kwok, Current Opinion in Structural Biology 50 (2018) 65–74. date_created: 2018-12-11T11:47:09Z date_published: 2018-06-01T00:00:00Z date_updated: 2023-09-11T14:07:03Z day: '01' department: - _id: MaLo doi: 10.1016/j.sbi.2017.12.002 external_id: isi: - '000443661300011' intvolume: ' 50' isi: 1 language: - iso: eng main_file_link: - open_access: '1' url: http://eprints.whiterose.ac.uk/125524/ month: '06' oa: 1 oa_version: Submitted Version page: 65 - 74 publication: Current Opinion in Structural Biology publication_status: published publisher: Elsevier publist_id: '7259' quality_controlled: '1' scopus_import: '1' status: public title: 'Glycosaminoglycans in extracellular matrix organisation: Are concepts from soft matter physics key to understanding the formation of perineuronal nets?' type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 50 year: '2018' ... --- _id: '448' abstract: - lang: eng text: Around 150 million years ago, eusocial termites evolved from within the cockroaches, 50 million years before eusocial Hymenoptera, such as bees and ants, appeared. Here, we report the 2-Gb genome of the German cockroach, Blattella germanica, and the 1.3-Gb genome of the drywood termite Cryptotermes secundus. We show evolutionary signatures of termite eusociality by comparing the genomes and transcriptomes of three termites and the cockroach against the background of 16 other eusocial and non-eusocial insects. Dramatic adaptive changes in genes underlying the production and perception of pheromones confirm the importance of chemical communication in the termites. These are accompanied by major changes in gene regulation and the molecular evolution of caste determination. Many of these results parallel molecular mechanisms of eusocial evolution in Hymenoptera. However, the specific solutions are remarkably different, thus revealing a striking case of convergence in one of the major evolutionary transitions in biological complexity. acknowledgement: We thank O. Niehuis for allowing use of the unpublished E. danica genome, J. Gadau and C. Smith for comments and advice on the manuscript, and J. Schmitz for assistance with analyses and proofreading the manuscript. J.K. thanks Charles Darwin University (Australia), especially S. Garnett and the Horticulture and Aquaculture team, for providing logistic support to collect C. secundus. The Parks and Wildlife Commission, Northern Territory, the Department of the Environment, Water, Heritage and the Arts gave permission to collect (Permit number 36401) and export (Permit WT2010-6997) the termites. USDA is an equal opportunity provider and employer. M.C.H. and E.J. are supported by DFG grant BO2544/11-1 to E.B.-B. J.K. is supported by University of Osnabrück and DFG grant KO1895/16-1. X.B. and M.-D.P. are supported by Spanish Ministerio de Economía y Competitividad (CGL2012-36251 and CGL2015-64727-P to X.B., and CGL2016-76011-R to M.-D.P.), including FEDER funds, and by Catalan Government (2014 SGR 619). C.S. is supported by grants from the US Department of Housing and Urban Development (NCHHU-0017-13), the National Science Foundation (IOS-1557864), the Alfred P. Sloan Foundation (2013-5-35 MBE), the National Institute of Environmental Health Sciences (P30ES025128) to the Center for Human Health and the Environment, and the Blanton J. Whitmire Endowment. M.P. is supported by a Villum Kann Rasmussen Young Investigator Fellowship (VKR10101). article_processing_charge: No author: - first_name: Mark full_name: Harrison, Mark last_name: Harrison - first_name: Evelien full_name: Jongepier, Evelien last_name: Jongepier - first_name: Hugh full_name: Robertson, Hugh last_name: Robertson - first_name: Nicolas full_name: Arning, Nicolas last_name: Arning - first_name: Tristan full_name: Bitard Feildel, Tristan last_name: Bitard Feildel - first_name: Hsu full_name: Chao, Hsu last_name: Chao - first_name: Christopher full_name: Childers, Christopher last_name: Childers - first_name: Huyen full_name: Dinh, Huyen last_name: Dinh - first_name: Harshavardhan full_name: Doddapaneni, Harshavardhan last_name: Doddapaneni - first_name: Shannon full_name: Dugan, Shannon last_name: Dugan - first_name: Johannes full_name: Gowin, Johannes last_name: Gowin - first_name: Carolin full_name: Greiner, Carolin last_name: Greiner - first_name: Yi full_name: Han, Yi last_name: Han - first_name: Haofu full_name: Hu, Haofu last_name: Hu - first_name: Daniel full_name: Hughes, Daniel last_name: Hughes - first_name: Ann K full_name: Huylmans, Ann K id: 4C0A3874-F248-11E8-B48F-1D18A9856A87 last_name: Huylmans orcid: 0000-0001-8871-4961 - first_name: Karsten full_name: Kemena, Karsten last_name: Kemena - first_name: Lukas full_name: Kremer, Lukas last_name: Kremer - first_name: Sandra full_name: Lee, Sandra last_name: Lee - first_name: Alberto full_name: López Ezquerra, Alberto last_name: López Ezquerra - first_name: Ludovic full_name: Mallet, Ludovic last_name: Mallet - first_name: Jose full_name: Monroy Kuhn, Jose last_name: Monroy Kuhn - first_name: Annabell full_name: Moser, Annabell last_name: Moser - first_name: Shwetha full_name: Murali, Shwetha last_name: Murali - first_name: Donna full_name: Muzny, Donna last_name: Muzny - first_name: Saria full_name: Otani, Saria last_name: Otani - first_name: Maria full_name: Piulachs, Maria last_name: Piulachs - first_name: Monica full_name: Poelchau, Monica last_name: Poelchau - first_name: Jiaxin full_name: Qu, Jiaxin last_name: Qu - first_name: Florentine full_name: Schaub, Florentine last_name: Schaub - first_name: Ayako full_name: Wada Katsumata, Ayako last_name: Wada Katsumata - first_name: Kim full_name: Worley, Kim last_name: Worley - first_name: Qiaolin full_name: Xie, Qiaolin last_name: Xie - first_name: Guillem full_name: Ylla, Guillem last_name: Ylla - first_name: Michael full_name: Poulsen, Michael last_name: Poulsen - first_name: Richard full_name: Gibbs, Richard last_name: Gibbs - first_name: Coby full_name: Schal, Coby last_name: Schal - first_name: Stephen full_name: Richards, Stephen last_name: Richards - first_name: Xavier full_name: Belles, Xavier last_name: Belles - first_name: Judith full_name: Korb, Judith last_name: Korb - first_name: Erich full_name: Bornberg Bauer, Erich last_name: Bornberg Bauer citation: ama: Harrison M, Jongepier E, Robertson H, et al. Hemimetabolous genomes reveal molecular basis of termite eusociality. Nature Ecology and Evolution. 2018;2(3):557-566. doi:10.1038/s41559-017-0459-1 apa: Harrison, M., Jongepier, E., Robertson, H., Arning, N., Bitard Feildel, T., Chao, H., … Bornberg Bauer, E. (2018). Hemimetabolous genomes reveal molecular basis of termite eusociality. Nature Ecology and Evolution. Springer Nature. https://doi.org/10.1038/s41559-017-0459-1 chicago: Harrison, Mark, Evelien Jongepier, Hugh Robertson, Nicolas Arning, Tristan Bitard Feildel, Hsu Chao, Christopher Childers, et al. “Hemimetabolous Genomes Reveal Molecular Basis of Termite Eusociality.” Nature Ecology and Evolution. Springer Nature, 2018. https://doi.org/10.1038/s41559-017-0459-1. ieee: M. Harrison et al., “Hemimetabolous genomes reveal molecular basis of termite eusociality,” Nature Ecology and Evolution, vol. 2, no. 3. Springer Nature, pp. 557–566, 2018. ista: Harrison M, Jongepier E, Robertson H, Arning N, Bitard Feildel T, Chao H, Childers C, Dinh H, Doddapaneni H, Dugan S, Gowin J, Greiner C, Han Y, Hu H, Hughes D, Huylmans AK, Kemena K, Kremer L, Lee S, López Ezquerra A, Mallet L, Monroy Kuhn J, Moser A, Murali S, Muzny D, Otani S, Piulachs M, Poelchau M, Qu J, Schaub F, Wada Katsumata A, Worley K, Xie Q, Ylla G, Poulsen M, Gibbs R, Schal C, Richards S, Belles X, Korb J, Bornberg Bauer E. 2018. Hemimetabolous genomes reveal molecular basis of termite eusociality. Nature Ecology and Evolution. 2(3), 557–566. mla: Harrison, Mark, et al. “Hemimetabolous Genomes Reveal Molecular Basis of Termite Eusociality.” Nature Ecology and Evolution, vol. 2, no. 3, Springer Nature, 2018, pp. 557–66, doi:10.1038/s41559-017-0459-1. short: M. Harrison, E. Jongepier, H. Robertson, N. Arning, T. Bitard Feildel, H. Chao, C. Childers, H. Dinh, H. Doddapaneni, S. Dugan, J. Gowin, C. Greiner, Y. Han, H. Hu, D. Hughes, A.K. Huylmans, K. Kemena, L. Kremer, S. Lee, A. López Ezquerra, L. Mallet, J. Monroy Kuhn, A. Moser, S. Murali, D. Muzny, S. Otani, M. Piulachs, M. Poelchau, J. Qu, F. Schaub, A. Wada Katsumata, K. Worley, Q. Xie, G. Ylla, M. Poulsen, R. Gibbs, C. Schal, S. Richards, X. Belles, J. Korb, E. Bornberg Bauer, Nature Ecology and Evolution 2 (2018) 557–566. date_created: 2018-12-11T11:46:32Z date_published: 2018-02-05T00:00:00Z date_updated: 2023-09-11T14:10:57Z day: '05' ddc: - '576' department: - _id: BeVi doi: 10.1038/s41559-017-0459-1 external_id: isi: - '000426559600026' file: - access_level: open_access checksum: 874953136ac125e65f37971d3cabc5b7 content_type: application/pdf creator: system date_created: 2018-12-12T10:09:08Z date_updated: 2020-07-14T12:46:30Z file_id: '4731' file_name: IST-2018-969-v1+1_2018_Huylmans_Hemimetabolous_genomes.pdf file_size: 3730583 relation: main_file file_date_updated: 2020-07-14T12:46:30Z has_accepted_license: '1' intvolume: ' 2' isi: 1 issue: '3' language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '02' oa: 1 oa_version: Published Version page: 557-566 publication: Nature Ecology and Evolution publication_status: published publisher: Springer Nature publist_id: '7375' pubrep_id: '969' quality_controlled: '1' related_material: record: - id: '9841' relation: research_data status: public scopus_import: '1' status: public title: Hemimetabolous genomes reveal molecular basis of termite eusociality tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 2 year: '2018' ... --- _id: '723' abstract: - lang: eng text: Escaping local optima is one of the major obstacles to function optimisation. Using the metaphor of a fitness landscape, local optima correspond to hills separated by fitness valleys that have to be overcome. We define a class of fitness valleys of tunable difficulty by considering their length, representing the Hamming path between the two optima and their depth, the drop in fitness. For this function class we present a runtime comparison between stochastic search algorithms using different search strategies. The (1+1) EA is a simple and well-studied evolutionary algorithm that has to jump across the valley to a point of higher fitness because it does not accept worsening moves (elitism). In contrast, the Metropolis algorithm and the Strong Selection Weak Mutation (SSWM) algorithm, a famous process in population genetics, are both able to cross the fitness valley by accepting worsening moves. We show that the runtime of the (1+1) EA depends critically on the length of the valley while the runtimes of the non-elitist algorithms depend crucially on the depth of the valley. Moreover, we show that both SSWM and Metropolis can also efficiently optimise a rugged function consisting of consecutive valleys. article_processing_charge: No author: - first_name: Pietro full_name: Oliveto, Pietro last_name: Oliveto - first_name: Tiago full_name: Paixao, Tiago id: 2C5658E6-F248-11E8-B48F-1D18A9856A87 last_name: Paixao orcid: 0000-0003-2361-3953 - first_name: Jorge full_name: Pérez Heredia, Jorge last_name: Pérez Heredia - first_name: Dirk full_name: Sudholt, Dirk last_name: Sudholt - first_name: Barbora full_name: Trubenova, Barbora id: 42302D54-F248-11E8-B48F-1D18A9856A87 last_name: Trubenova orcid: 0000-0002-6873-2967 citation: ama: Oliveto P, Paixao T, Pérez Heredia J, Sudholt D, Trubenova B. How to escape local optima in black box optimisation when non elitism outperforms elitism. Algorithmica. 2018;80(5):1604-1633. doi:10.1007/s00453-017-0369-2 apa: Oliveto, P., Paixao, T., Pérez Heredia, J., Sudholt, D., & Trubenova, B. (2018). How to escape local optima in black box optimisation when non elitism outperforms elitism. Algorithmica. Springer. https://doi.org/10.1007/s00453-017-0369-2 chicago: Oliveto, Pietro, Tiago Paixao, Jorge Pérez Heredia, Dirk Sudholt, and Barbora Trubenova. “How to Escape Local Optima in Black Box Optimisation When Non Elitism Outperforms Elitism.” Algorithmica. Springer, 2018. https://doi.org/10.1007/s00453-017-0369-2. ieee: P. Oliveto, T. Paixao, J. Pérez Heredia, D. Sudholt, and B. Trubenova, “How to escape local optima in black box optimisation when non elitism outperforms elitism,” Algorithmica, vol. 80, no. 5. Springer, pp. 1604–1633, 2018. ista: Oliveto P, Paixao T, Pérez Heredia J, Sudholt D, Trubenova B. 2018. How to escape local optima in black box optimisation when non elitism outperforms elitism. Algorithmica. 80(5), 1604–1633. mla: Oliveto, Pietro, et al. “How to Escape Local Optima in Black Box Optimisation When Non Elitism Outperforms Elitism.” Algorithmica, vol. 80, no. 5, Springer, 2018, pp. 1604–33, doi:10.1007/s00453-017-0369-2. short: P. Oliveto, T. Paixao, J. Pérez Heredia, D. Sudholt, B. Trubenova, Algorithmica 80 (2018) 1604–1633. date_created: 2018-12-11T11:48:09Z date_published: 2018-05-01T00:00:00Z date_updated: 2023-09-11T14:11:35Z day: '01' ddc: - '576' department: - _id: NiBa - _id: CaGu doi: 10.1007/s00453-017-0369-2 ec_funded: 1 external_id: isi: - '000428239300010' file: - access_level: open_access checksum: 7d92f5d7be81e387edeec4f06442791c content_type: application/pdf creator: system date_created: 2018-12-12T10:08:14Z date_updated: 2020-07-14T12:47:54Z file_id: '4674' file_name: IST-2018-1014-v1+1_2018_Paixao_Escape.pdf file_size: 691245 relation: main_file file_date_updated: 2020-07-14T12:47:54Z has_accepted_license: '1' intvolume: ' 80' isi: 1 issue: '5' language: - iso: eng month: '05' oa: 1 oa_version: Published Version page: 1604 - 1633 project: - _id: 25B1EC9E-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '618091' name: Speed of Adaptation in Population Genetics and Evolutionary Computation publication: Algorithmica publication_status: published publisher: Springer publist_id: '6957' pubrep_id: '1014' quality_controlled: '1' scopus_import: '1' status: public title: How to escape local optima in black box optimisation when non elitism outperforms elitism tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 80 year: '2018' ... --- _id: '321' abstract: - lang: eng text: The twelve papers in this special section focus on learning systems with shared information for computer vision and multimedia communication analysis. In the real world, a realistic setting for computer vision or multimedia recognition problems is that we have some classes containing lots of training data and many classes containing a small amount of training data. Therefore, how to use frequent classes to help learning rare classes for which it is harder to collect the training data is an open question. Learning with shared information is an emerging topic in machine learning, computer vision and multimedia analysis. There are different levels of components that can be shared during concept modeling and machine learning stages, such as sharing generic object parts, sharing attributes, sharing transformations, sharing regularization parameters and sharing training examples, etc. Regarding the specific methods, multi-task learning, transfer learning and deep learning can be seen as using different strategies to share information. These learning with shared information methods are very effective in solving real-world large-scale problems. article_processing_charge: No article_type: original author: - first_name: Trevor full_name: Darrell, Trevor last_name: Darrell - first_name: Christoph full_name: Lampert, Christoph id: 40C20FD2-F248-11E8-B48F-1D18A9856A87 last_name: Lampert orcid: 0000-0001-8622-7887 - first_name: Nico full_name: Sebe, Nico last_name: Sebe - first_name: Ying full_name: Wu, Ying last_name: Wu - first_name: Yan full_name: Yan, Yan last_name: Yan citation: ama: Darrell T, Lampert C, Sebe N, Wu Y, Yan Y. Guest editors’ introduction to the special section on learning with Shared information for computer vision and multimedia analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2018;40(5):1029-1031. doi:10.1109/TPAMI.2018.2804998 apa: Darrell, T., Lampert, C., Sebe, N., Wu, Y., & Yan, Y. (2018). Guest editors’ introduction to the special section on learning with Shared information for computer vision and multimedia analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE. https://doi.org/10.1109/TPAMI.2018.2804998 chicago: Darrell, Trevor, Christoph Lampert, Nico Sebe, Ying Wu, and Yan Yan. “Guest Editors’ Introduction to the Special Section on Learning with Shared Information for Computer Vision and Multimedia Analysis.” IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE, 2018. https://doi.org/10.1109/TPAMI.2018.2804998. ieee: T. Darrell, C. Lampert, N. Sebe, Y. Wu, and Y. Yan, “Guest editors’ introduction to the special section on learning with Shared information for computer vision and multimedia analysis,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 5. IEEE, pp. 1029–1031, 2018. ista: Darrell T, Lampert C, Sebe N, Wu Y, Yan Y. 2018. Guest editors’ introduction to the special section on learning with Shared information for computer vision and multimedia analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence. 40(5), 1029–1031. mla: Darrell, Trevor, et al. “Guest Editors’ Introduction to the Special Section on Learning with Shared Information for Computer Vision and Multimedia Analysis.” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 5, IEEE, 2018, pp. 1029–31, doi:10.1109/TPAMI.2018.2804998. short: T. Darrell, C. Lampert, N. Sebe, Y. Wu, Y. Yan, IEEE Transactions on Pattern Analysis and Machine Intelligence 40 (2018) 1029–1031. date_created: 2018-12-11T11:45:48Z date_published: 2018-05-01T00:00:00Z date_updated: 2023-09-11T14:07:54Z day: '01' ddc: - '000' department: - _id: ChLa doi: 10.1109/TPAMI.2018.2804998 external_id: isi: - '000428901200001' file: - access_level: open_access checksum: b19c75da06faf3291a3ca47dfa50ef63 content_type: application/pdf creator: dernst date_created: 2020-05-14T12:50:48Z date_updated: 2020-07-14T12:46:03Z file_id: '7835' file_name: 2018_IEEE_Darrell.pdf file_size: 141724 relation: main_file file_date_updated: 2020-07-14T12:46:03Z has_accepted_license: '1' intvolume: ' 40' isi: 1 issue: '5' language: - iso: eng month: '05' oa: 1 oa_version: Published Version page: 1029 - 1031 publication: IEEE Transactions on Pattern Analysis and Machine Intelligence publication_status: published publisher: IEEE publist_id: '7544' quality_controlled: '1' scopus_import: '1' status: public title: Guest editors' introduction to the special section on learning with Shared information for computer vision and multimedia analysis type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 40 year: '2018' ... --- _id: '9841' abstract: - lang: eng text: Around 150 million years ago, eusocial termites evolved from within the cockroaches, 50 million years before eusocial Hymenoptera, such as bees and ants, appeared. Here, we report the 2-Gb genome of the German cockroach, Blattella germanica, and the 1.3-Gb genome of the drywood termite Cryptotermes secundus. We show evolutionary signatures of termite eusociality by comparing the genomes and transcriptomes of three termites and the cockroach against the background of 16 other eusocial and non-eusocial insects. Dramatic adaptive changes in genes underlying the production and perception of pheromones confirm the importance of chemical communication in the termites. These are accompanied by major changes in gene regulation and the molecular evolution of caste determination. Many of these results parallel molecular mechanisms of eusocial evolution in Hymenoptera. However, the specific solutions are remarkably different, thus revealing a striking case of convergence in one of the major evolutionary transitions in biological complexity. article_processing_charge: No author: - first_name: Mark C. full_name: Harrison, Mark C. last_name: Harrison - first_name: Evelien full_name: Jongepier, Evelien last_name: Jongepier - first_name: Hugh M. full_name: Robertson, Hugh M. last_name: Robertson - first_name: Nicolas full_name: Arning, Nicolas last_name: Arning - first_name: Tristan full_name: Bitard-Feildel, Tristan last_name: Bitard-Feildel - first_name: Hsu full_name: Chao, Hsu last_name: Chao - first_name: Christopher P. full_name: Childers, Christopher P. last_name: Childers - first_name: Huyen full_name: Dinh, Huyen last_name: Dinh - first_name: Harshavardhan full_name: Doddapaneni, Harshavardhan last_name: Doddapaneni - first_name: Shannon full_name: Dugan, Shannon last_name: Dugan - first_name: Johannes full_name: Gowin, Johannes last_name: Gowin - first_name: Carolin full_name: Greiner, Carolin last_name: Greiner - first_name: Yi full_name: Han, Yi last_name: Han - first_name: Haofu full_name: Hu, Haofu last_name: Hu - first_name: Daniel S. T. full_name: Hughes, Daniel S. T. last_name: Hughes - first_name: Ann K full_name: Huylmans, Ann K id: 4C0A3874-F248-11E8-B48F-1D18A9856A87 last_name: Huylmans orcid: 0000-0001-8871-4961 - first_name: Carsten full_name: Kemena, Carsten last_name: Kemena - first_name: Lukas P. M. full_name: Kremer, Lukas P. M. last_name: Kremer - first_name: Sandra L. full_name: Lee, Sandra L. last_name: Lee - first_name: Alberto full_name: Lopez-Ezquerra, Alberto last_name: Lopez-Ezquerra - first_name: Ludovic full_name: Mallet, Ludovic last_name: Mallet - first_name: Jose M. full_name: Monroy-Kuhn, Jose M. last_name: Monroy-Kuhn - first_name: Annabell full_name: Moser, Annabell last_name: Moser - first_name: Shwetha C. full_name: Murali, Shwetha C. last_name: Murali - first_name: Donna M. full_name: Muzny, Donna M. last_name: Muzny - first_name: Saria full_name: Otani, Saria last_name: Otani - first_name: Maria-Dolors full_name: Piulachs, Maria-Dolors last_name: Piulachs - first_name: Monica full_name: Poelchau, Monica last_name: Poelchau - first_name: Jiaxin full_name: Qu, Jiaxin last_name: Qu - first_name: Florentine full_name: Schaub, Florentine last_name: Schaub - first_name: Ayako full_name: Wada-Katsumata, Ayako last_name: Wada-Katsumata - first_name: Kim C. full_name: Worley, Kim C. last_name: Worley - first_name: Qiaolin full_name: Xie, Qiaolin last_name: Xie - first_name: Guillem full_name: Ylla, Guillem last_name: Ylla - first_name: Michael full_name: Poulsen, Michael last_name: Poulsen - first_name: Richard A. full_name: Gibbs, Richard A. last_name: Gibbs - first_name: Coby full_name: Schal, Coby last_name: Schal - first_name: Stephen full_name: Richards, Stephen last_name: Richards - first_name: Xavier full_name: Belles, Xavier last_name: Belles - first_name: Judith full_name: Korb, Judith last_name: Korb - first_name: Erich full_name: Bornberg-Bauer, Erich last_name: Bornberg-Bauer citation: ama: 'Harrison MC, Jongepier E, Robertson HM, et al. Data from: Hemimetabolous genomes reveal molecular basis of termite eusociality. 2018. doi:10.5061/dryad.51d4r' apa: 'Harrison, M. C., Jongepier, E., Robertson, H. M., Arning, N., Bitard-Feildel, T., Chao, H., … Bornberg-Bauer, E. (2018). Data from: Hemimetabolous genomes reveal molecular basis of termite eusociality. Dryad. https://doi.org/10.5061/dryad.51d4r' chicago: 'Harrison, Mark C., Evelien Jongepier, Hugh M. Robertson, Nicolas Arning, Tristan Bitard-Feildel, Hsu Chao, Christopher P. Childers, et al. “Data from: Hemimetabolous Genomes Reveal Molecular Basis of Termite Eusociality.” Dryad, 2018. https://doi.org/10.5061/dryad.51d4r.' ieee: 'M. C. Harrison et al., “Data from: Hemimetabolous genomes reveal molecular basis of termite eusociality.” Dryad, 2018.' ista: 'Harrison MC, Jongepier E, Robertson HM, Arning N, Bitard-Feildel T, Chao H, Childers CP, Dinh H, Doddapaneni H, Dugan S, Gowin J, Greiner C, Han Y, Hu H, Hughes DST, Huylmans AK, Kemena C, Kremer LPM, Lee SL, Lopez-Ezquerra A, Mallet L, Monroy-Kuhn JM, Moser A, Murali SC, Muzny DM, Otani S, Piulachs M-D, Poelchau M, Qu J, Schaub F, Wada-Katsumata A, Worley KC, Xie Q, Ylla G, Poulsen M, Gibbs RA, Schal C, Richards S, Belles X, Korb J, Bornberg-Bauer E. 2018. Data from: Hemimetabolous genomes reveal molecular basis of termite eusociality, Dryad, 10.5061/dryad.51d4r.' mla: 'Harrison, Mark C., et al. Data from: Hemimetabolous Genomes Reveal Molecular Basis of Termite Eusociality. Dryad, 2018, doi:10.5061/dryad.51d4r.' short: M.C. Harrison, E. Jongepier, H.M. Robertson, N. Arning, T. Bitard-Feildel, H. Chao, C.P. Childers, H. Dinh, H. Doddapaneni, S. Dugan, J. Gowin, C. Greiner, Y. Han, H. Hu, D.S.T. Hughes, A.K. Huylmans, C. Kemena, L.P.M. Kremer, S.L. Lee, A. Lopez-Ezquerra, L. Mallet, J.M. Monroy-Kuhn, A. Moser, S.C. Murali, D.M. Muzny, S. Otani, M.-D. Piulachs, M. Poelchau, J. Qu, F. Schaub, A. Wada-Katsumata, K.C. Worley, Q. Xie, G. Ylla, M. Poulsen, R.A. Gibbs, C. Schal, S. Richards, X. Belles, J. Korb, E. Bornberg-Bauer, (2018). date_created: 2021-08-09T13:13:48Z date_published: 2018-12-12T00:00:00Z date_updated: 2023-09-11T14:10:56Z day: '12' department: - _id: BeVi doi: 10.5061/dryad.51d4r main_file_link: - open_access: '1' url: https://doi.org/10.5061/dryad.51d4r month: '12' oa: 1 oa_version: Published Version publisher: Dryad related_material: record: - id: '448' relation: used_in_publication status: public status: public title: 'Data from: Hemimetabolous genomes reveal molecular basis of termite eusociality' type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2018' ...