[{"month":"11","date_created":"2023-11-19T23:00:54Z","status":"public","intvolume":"        14","file_date_updated":"2023-11-20T11:22:52Z","article_type":"original","publisher":"Elsevier","volume":14,"issue":"11","project":[{"call_identifier":"H2020","_id":"62935a00-2b32-11ec-9570-eff30fa39068","grant_number":"725746","name":"Quantitative analysis of DNA methylation maintenance with chromatin"}],"abstract":[{"lang":"eng","text":"Methylation of CG dinucleotides (mCGs), which regulates eukaryotic genome functions, is epigenetically propagated by Dnmt1/MET1 methyltransferases. How mCG is established and transmitted across generations despite imperfect enzyme fidelity is unclear. Whether mCG variation in natural populations is governed by genetic or epigenetic inheritance also remains mysterious. Here, we show that MET1 de novo activity, which is enhanced by existing proximate methylation, seeds and stabilizes mCG in Arabidopsis thaliana genes. MET1 activity is restricted by active demethylation and suppressed by histone variant H2A.Z, producing localized mCG patterns. Based on these observations, we develop a stochastic mathematical model that precisely recapitulates mCG inheritance dynamics and predicts intragenic mCG patterns and their population-scale variation given only CG site spacing. Our results demonstrate that intragenic mCG establishment, inheritance, and variance constitute a unified epigenetic process, revealing that intragenic mCG undergoes large, millennia-long epigenetic fluctuations and can therefore mediate evolution on this timescale."}],"publication_status":"published","pmid":1,"publication":"Cell Systems","title":"Millennia-long epigenetic fluctuations generate intragenic DNA methylation variance in Arabidopsis populations","_id":"14551","oa":1,"ddc":["570"],"tmp":{"image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"year":"2023","citation":{"mla":"Briffa, Amy, et al. “Millennia-Long Epigenetic Fluctuations Generate Intragenic DNA Methylation Variance in Arabidopsis Populations.” <i>Cell Systems</i>, vol. 14, no. 11, Elsevier, 2023, pp. 953–67, doi:<a href=\"https://doi.org/10.1016/j.cels.2023.10.007\">10.1016/j.cels.2023.10.007</a>.","apa":"Briffa, A., Hollwey, E., Shahzad, Z., Moore, J. D., Lyons, D. B., Howard, M., &#38; Zilberman, D. (2023). Millennia-long epigenetic fluctuations generate intragenic DNA methylation variance in Arabidopsis populations. <i>Cell Systems</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.cels.2023.10.007\">https://doi.org/10.1016/j.cels.2023.10.007</a>","ama":"Briffa A, Hollwey E, Shahzad Z, et al. Millennia-long epigenetic fluctuations generate intragenic DNA methylation variance in Arabidopsis populations. <i>Cell Systems</i>. 2023;14(11):953-967. doi:<a href=\"https://doi.org/10.1016/j.cels.2023.10.007\">10.1016/j.cels.2023.10.007</a>","ieee":"A. Briffa <i>et al.</i>, “Millennia-long epigenetic fluctuations generate intragenic DNA methylation variance in Arabidopsis populations,” <i>Cell Systems</i>, vol. 14, no. 11. Elsevier, pp. 953–967, 2023.","chicago":"Briffa, Amy, Elizabeth Hollwey, Zaigham Shahzad, Jonathan D. Moore, David B. Lyons, Martin Howard, and Daniel Zilberman. “Millennia-Long Epigenetic Fluctuations Generate Intragenic DNA Methylation Variance in Arabidopsis Populations.” <i>Cell Systems</i>. Elsevier, 2023. <a href=\"https://doi.org/10.1016/j.cels.2023.10.007\">https://doi.org/10.1016/j.cels.2023.10.007</a>.","short":"A. Briffa, E. Hollwey, Z. Shahzad, J.D. Moore, D.B. Lyons, M. Howard, D. Zilberman, Cell Systems 14 (2023) 953–967.","ista":"Briffa A, Hollwey E, Shahzad Z, Moore JD, Lyons DB, Howard M, Zilberman D. 2023. Millennia-long epigenetic fluctuations generate intragenic DNA methylation variance in Arabidopsis populations. Cell Systems. 14(11), 953–967."},"quality_controlled":"1","author":[{"first_name":"Amy","last_name":"Briffa","full_name":"Briffa, Amy"},{"last_name":"Hollwey","first_name":"Elizabeth","id":"b8c4f54b-e484-11eb-8fdc-a54df64ef6dd","full_name":"Hollwey, Elizabeth"},{"last_name":"Shahzad","first_name":"Zaigham","full_name":"Shahzad, Zaigham"},{"full_name":"Moore, Jonathan D.","last_name":"Moore","first_name":"Jonathan D."},{"full_name":"Lyons, David B.","first_name":"David B.","last_name":"Lyons"},{"last_name":"Howard","first_name":"Martin","full_name":"Howard, Martin"},{"id":"6973db13-dd5f-11ea-814e-b3e5455e9ed1","full_name":"Zilberman, Daniel","orcid":"0000-0002-0123-8649","first_name":"Daniel","last_name":"Zilberman"}],"scopus_import":"1","publication_identifier":{"eissn":["2405-4720"],"issn":["2405-4712"]},"external_id":{"pmid":["37944515"]},"file":[{"date_created":"2023-11-20T11:22:52Z","relation":"main_file","content_type":"application/pdf","creator":"dernst","file_size":5587897,"date_updated":"2023-11-20T11:22:52Z","file_id":"14580","success":1,"access_level":"open_access","checksum":"101fdac59e6f1102d68ef91f2b5bd51a","file_name":"2023_CellSystems_Briffa.pdf"}],"date_published":"2023-11-15T00:00:00Z","page":"953-967","acknowledgement":"We would like to thank Xiaoqi Feng, Ander Movilla Miangolarra, and Suzanne de Bruijn for discussions. This work was supported by BBSRC Institute Strategic Programme GEN (BB/P013511/1) to M.H. and D.Z. and by a European Research Council grant MaintainMeth (725746) to D.Z.","ec_funded":1,"department":[{"_id":"DaZi"}],"has_accepted_license":"1","language":[{"iso":"eng"}],"doi":"10.1016/j.cels.2023.10.007","oa_version":"Published Version","type":"journal_article","date_updated":"2023-11-20T11:24:34Z","day":"15","article_processing_charge":"Yes (via OA deal)","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87"},{"external_id":{"pmid":["35452605"],"isi":["000814124400002"]},"date_published":"2022-06-15T00:00:00Z","page":"438-453.e5","scopus_import":"1","publication_identifier":{"issn":["2405-4712"],"eissn":["2405-4720"]},"oa_version":"Published Version","type":"journal_article","date_updated":"2023-08-03T07:19:43Z","day":"15","article_processing_charge":"No","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","acknowledgement":"D.J.A. thanks Wayne K. Potts, Alan R. Rogers, Kristen Hawkes, Ryk Ward, and Jon Seger for inspiring a young undergraduate to apply evolutionary theory to intraorganism development. Supported by the Paul G. Allen Frontiers Group (University of Washington); NIH R00HG010152 (Dartmouth); and NÖ Forschung und Bildung n[f+b] life science call grant (C13-002) and the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program 725780 LinPro to S.H.","ec_funded":1,"department":[{"_id":"SiHi"}],"language":[{"iso":"eng"}],"doi":"10.1016/j.cels.2022.03.006","article_type":"original","publisher":"Elsevier","volume":13,"issue":"6","month":"06","date_created":"2022-06-19T22:01:57Z","status":"public","intvolume":"        13","isi":1,"year":"2022","citation":{"apa":"Anderson, D. J., Pauler, F., Mckenna, A., Shendure, J., Hippenmeyer, S., &#38; Horwitz, M. S. (2022). Simultaneous brain cell type and lineage determined by scRNA-seq reveals stereotyped cortical development. <i>Cell Systems</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.cels.2022.03.006\">https://doi.org/10.1016/j.cels.2022.03.006</a>","mla":"Anderson, Donovan J., et al. “Simultaneous Brain Cell Type and Lineage Determined by ScRNA-Seq Reveals Stereotyped Cortical Development.” <i>Cell Systems</i>, vol. 13, no. 6, Elsevier, 2022, p. 438–453.e5, doi:<a href=\"https://doi.org/10.1016/j.cels.2022.03.006\">10.1016/j.cels.2022.03.006</a>.","ista":"Anderson DJ, Pauler F, Mckenna A, Shendure J, Hippenmeyer S, Horwitz MS. 2022. Simultaneous brain cell type and lineage determined by scRNA-seq reveals stereotyped cortical development. Cell Systems. 13(6), 438–453.e5.","chicago":"Anderson, Donovan J., Florian Pauler, Aaron Mckenna, Jay Shendure, Simon Hippenmeyer, and Marshall S. Horwitz. “Simultaneous Brain Cell Type and Lineage Determined by ScRNA-Seq Reveals Stereotyped Cortical Development.” <i>Cell Systems</i>. Elsevier, 2022. <a href=\"https://doi.org/10.1016/j.cels.2022.03.006\">https://doi.org/10.1016/j.cels.2022.03.006</a>.","short":"D.J. Anderson, F. Pauler, A. Mckenna, J. Shendure, S. Hippenmeyer, M.S. Horwitz, Cell Systems 13 (2022) 438–453.e5.","ama":"Anderson DJ, Pauler F, Mckenna A, Shendure J, Hippenmeyer S, Horwitz MS. Simultaneous brain cell type and lineage determined by scRNA-seq reveals stereotyped cortical development. <i>Cell Systems</i>. 2022;13(6):438-453.e5. doi:<a href=\"https://doi.org/10.1016/j.cels.2022.03.006\">10.1016/j.cels.2022.03.006</a>","ieee":"D. J. Anderson, F. Pauler, A. Mckenna, J. Shendure, S. Hippenmeyer, and M. S. Horwitz, “Simultaneous brain cell type and lineage determined by scRNA-seq reveals stereotyped cortical development,” <i>Cell Systems</i>, vol. 13, no. 6. Elsevier, p. 438–453.e5, 2022."},"main_file_link":[{"open_access":"1","url":"https://doi.org/10.1016/j.cels.2022.03.006"}],"author":[{"full_name":"Anderson, Donovan J.","first_name":"Donovan J.","last_name":"Anderson"},{"full_name":"Pauler, Florian","id":"48EA0138-F248-11E8-B48F-1D18A9856A87","first_name":"Florian","last_name":"Pauler"},{"last_name":"Mckenna","first_name":"Aaron","full_name":"Mckenna, Aaron"},{"full_name":"Shendure, Jay","first_name":"Jay","last_name":"Shendure"},{"last_name":"Hippenmeyer","first_name":"Simon","full_name":"Hippenmeyer, Simon","orcid":"0000-0003-2279-1061","id":"37B36620-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Horwitz, Marshall S.","first_name":"Marshall S.","last_name":"Horwitz"}],"quality_controlled":"1","project":[{"grant_number":"725780","name":"Principles of Neural Stem Cell Lineage Progression in Cerebral Cortex Development","_id":"260018B0-B435-11E9-9278-68D0E5697425","call_identifier":"H2020"},{"_id":"25D92700-B435-11E9-9278-68D0E5697425","grant_number":"LS13-002","name":"Mapping Cell-Type Specificity of the Genomic Imprintome in the Brain"}],"abstract":[{"lang":"eng","text":"Mutations are acquired frequently, such that each cell's genome inscribes its history of cell divisions. Common genomic alterations involve loss of heterozygosity (LOH). LOH accumulates throughout the genome, offering large encoding capacity for inferring cell lineage. Using only single-cell RNA sequencing (scRNA-seq) of mouse brain cells, we found that LOH events spanning multiple genes are revealed as tracts of monoallelically expressed, constitutionally heterozygous single-nucleotide variants (SNVs). We simultaneously inferred cell lineage and marked developmental time points based on X chromosome inactivation and the total number of LOH events while identifying cell types from gene expression patterns. Our results are consistent with progenitor cells giving rise to multiple cortical cell types through stereotyped expansion and distinct waves of neurogenesis. This type of retrospective analysis could be incorporated into scRNA-seq pipelines and, compared with experimental approaches for determining lineage in model organisms, is applicable where genetic engineering is prohibited, such as humans."}],"publication_status":"published","pmid":1,"publication":"Cell Systems","title":"Simultaneous brain cell type and lineage determined by scRNA-seq reveals stereotyped cortical development","_id":"11449","oa":1},{"page":"423-433.e1-e3","date_published":"2019-11-27T00:00:00Z","file":[{"relation":"main_file","date_created":"2019-11-15T10:57:42Z","creator":"dernst","content_type":"application/pdf","file_size":4238460,"date_updated":"2020-07-14T12:47:48Z","file_id":"7027","checksum":"7a11d6c2f9523d65b049512d61733178","file_name":"2019_CellSystems_Lukacisin.pdf","access_level":"open_access"}],"external_id":{"isi":["000499495400003"]},"publication_identifier":{"issn":["2405-4712"]},"scopus_import":"1","article_processing_charge":"No","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","day":"27","type":"journal_article","date_updated":"2023-08-30T07:24:58Z","oa_version":"Published Version","language":[{"iso":"eng"}],"doi":"10.1016/j.cels.2019.10.004","has_accepted_license":"1","department":[{"_id":"ToBo"}],"acknowledged_ssus":[{"_id":"LifeSc"}],"issue":"5","volume":9,"publisher":"Cell Press","article_type":"original","file_date_updated":"2020-07-14T12:47:48Z","isi":1,"intvolume":"         9","status":"public","date_created":"2019-11-15T10:51:42Z","month":"11","quality_controlled":"1","author":[{"id":"298FFE8C-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6549-4177","full_name":"Lukacisin, Martin","first_name":"Martin","last_name":"Lukacisin"},{"orcid":"0000-0003-4398-476X","full_name":"Bollenbach, Tobias","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","first_name":"Tobias","last_name":"Bollenbach"}],"citation":{"apa":"Lukacisin, M., &#38; Bollenbach, M. T. (2019). Emergent gene expression responses to drug combinations predict higher-order drug interactions. <i>Cell Systems</i>. Cell Press. <a href=\"https://doi.org/10.1016/j.cels.2019.10.004\">https://doi.org/10.1016/j.cels.2019.10.004</a>","mla":"Lukacisin, Martin, and Mark Tobias Bollenbach. “Emergent Gene Expression Responses to Drug Combinations Predict Higher-Order Drug Interactions.” <i>Cell Systems</i>, vol. 9, no. 5, Cell Press, 2019, pp. 423-433.e1-e3, doi:<a href=\"https://doi.org/10.1016/j.cels.2019.10.004\">10.1016/j.cels.2019.10.004</a>.","ieee":"M. Lukacisin and M. T. Bollenbach, “Emergent gene expression responses to drug combinations predict higher-order drug interactions,” <i>Cell Systems</i>, vol. 9, no. 5. Cell Press, pp. 423-433.e1-e3, 2019.","ama":"Lukacisin M, Bollenbach MT. Emergent gene expression responses to drug combinations predict higher-order drug interactions. <i>Cell Systems</i>. 2019;9(5):423-433.e1-e3. doi:<a href=\"https://doi.org/10.1016/j.cels.2019.10.004\">10.1016/j.cels.2019.10.004</a>","short":"M. Lukacisin, M.T. Bollenbach, Cell Systems 9 (2019) 423-433.e1-e3.","chicago":"Lukacisin, Martin, and Mark Tobias Bollenbach. “Emergent Gene Expression Responses to Drug Combinations Predict Higher-Order Drug Interactions.” <i>Cell Systems</i>. Cell Press, 2019. <a href=\"https://doi.org/10.1016/j.cels.2019.10.004\">https://doi.org/10.1016/j.cels.2019.10.004</a>.","ista":"Lukacisin M, Bollenbach MT. 2019. Emergent gene expression responses to drug combinations predict higher-order drug interactions. Cell Systems. 9(5), 423-433.e1-e3."},"year":"2019","tmp":{"image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"ddc":["570"],"oa":1,"_id":"7026","title":"Emergent gene expression responses to drug combinations predict higher-order drug interactions","publication":"Cell Systems","publication_status":"published","abstract":[{"text":"Effective design of combination therapies requires understanding the changes in cell physiology that result from drug interactions. Here, we show that the genome-wide transcriptional response to combinations of two drugs, measured at a rigorously controlled growth rate, can predict higher-order antagonism with a third drug in Saccharomyces cerevisiae. Using isogrowth profiling, over 90% of the variation in cellular response can be decomposed into three principal components (PCs) that have clear biological interpretations. We demonstrate that the third PC captures emergent transcriptional programs that are dependent on both drugs and can predict antagonism with a third drug targeting the emergent pathway. We further show that emergent gene expression patterns are most pronounced at a drug ratio where the drug interaction is strongest, providing a guideline for future measurements. Our results provide a readily applicable recipe for uncovering emergent responses in other systems and for higher-order drug combinations. A record of this paper’s transparent peer review process is included in the Supplemental Information.","lang":"eng"}],"project":[{"call_identifier":"FWF","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","name":"Revealing the mechanisms underlying drug interactions","grant_number":"P27201-B22"},{"_id":"25EB3A80-B435-11E9-9278-68D0E5697425","name":"Revealing the fundamental limits of cell growth","grant_number":"RGP0042/2013"}]},{"doi":"10.1016/j.cels.2015.08.012","language":[{"iso":"eng"}],"article_processing_charge":"No","user_id":"72615eeb-f1f3-11ec-aa25-d4573ddc34fd","day":"23","date_updated":"2022-07-18T08:44:07Z","type":"journal_article","oa_version":"Published Version","publication_identifier":{"issn":["2405-4712"]},"scopus_import":"1","page":"P224-237","date_published":"2015-09-23T00:00:00Z","external_id":{"pmid":["27135913"]},"keyword":["Cell Biology","Histology","Pathology and Forensic Medicine"],"oa":1,"_id":"11078","title":"Integrated transcriptome and proteome analyses reveal organ-specific proteome deterioration in old rats","publication":"Cell Systems","pmid":1,"publication_status":"published","abstract":[{"lang":"eng","text":"Aging is associated with the decline of protein, cell, and organ function. Here, we use an integrated approach to characterize gene expression, bulk translation, and cell biology in the brains and livers of young and old rats. We identify 468 differences in protein abundance between young and old animals. The majority are a consequence of altered translation output, that is, the combined effect of changes in transcript abundance and translation efficiency. In addition, we identify 130 proteins whose overall abundance remains unchanged but whose sub-cellular localization, phosphorylation state, or splice-form varies. While some protein-level differences appear to be a generic property of the rats’ chronological age, the majority are specific to one organ. These may be a consequence of the organ’s physiology or the chronological age of the cells within the tissue. Taken together, our study provides an initial view of the proteome at the molecular, sub-cellular, and organ level in young and old rats."}],"author":[{"full_name":"Ori, Alessandro","last_name":"Ori","first_name":"Alessandro"},{"last_name":"Toyama","first_name":"Brandon H.","full_name":"Toyama, Brandon H."},{"full_name":"Harris, Michael S.","first_name":"Michael S.","last_name":"Harris"},{"last_name":"Bock","first_name":"Thomas","full_name":"Bock, Thomas"},{"last_name":"Iskar","first_name":"Murat","full_name":"Iskar, Murat"},{"last_name":"Bork","first_name":"Peer","full_name":"Bork, Peer"},{"first_name":"Nicholas T.","last_name":"Ingolia","full_name":"Ingolia, Nicholas T."},{"orcid":"0000-0002-2111-992X","full_name":"HETZER, Martin W","id":"86c0d31b-b4eb-11ec-ac5a-eae7b2e135ed","last_name":"HETZER","first_name":"Martin W"},{"last_name":"Beck","first_name":"Martin","full_name":"Beck, Martin"}],"quality_controlled":"1","extern":"1","main_file_link":[{"url":"https://doi.org/10.1016/j.cels.2015.08.012","open_access":"1"}],"citation":{"ieee":"A. Ori <i>et al.</i>, “Integrated transcriptome and proteome analyses reveal organ-specific proteome deterioration in old rats,” <i>Cell Systems</i>, vol. 1, no. 3. Elsevier, pp. P224-237, 2015.","ama":"Ori A, Toyama BH, Harris MS, et al. Integrated transcriptome and proteome analyses reveal organ-specific proteome deterioration in old rats. <i>Cell Systems</i>. 2015;1(3):P224-237. doi:<a href=\"https://doi.org/10.1016/j.cels.2015.08.012\">10.1016/j.cels.2015.08.012</a>","ista":"Ori A, Toyama BH, Harris MS, Bock T, Iskar M, Bork P, Ingolia NT, Hetzer M, Beck M. 2015. Integrated transcriptome and proteome analyses reveal organ-specific proteome deterioration in old rats. Cell Systems. 1(3), P224-237.","chicago":"Ori, Alessandro, Brandon H. Toyama, Michael S. Harris, Thomas Bock, Murat Iskar, Peer Bork, Nicholas T. Ingolia, Martin Hetzer, and Martin Beck. “Integrated Transcriptome and Proteome Analyses Reveal Organ-Specific Proteome Deterioration in Old Rats.” <i>Cell Systems</i>. Elsevier, 2015. <a href=\"https://doi.org/10.1016/j.cels.2015.08.012\">https://doi.org/10.1016/j.cels.2015.08.012</a>.","short":"A. Ori, B.H. Toyama, M.S. Harris, T. Bock, M. Iskar, P. Bork, N.T. Ingolia, M. Hetzer, M. Beck, Cell Systems 1 (2015) P224-237.","mla":"Ori, Alessandro, et al. “Integrated Transcriptome and Proteome Analyses Reveal Organ-Specific Proteome Deterioration in Old Rats.” <i>Cell Systems</i>, vol. 1, no. 3, Elsevier, 2015, pp. P224-237, doi:<a href=\"https://doi.org/10.1016/j.cels.2015.08.012\">10.1016/j.cels.2015.08.012</a>.","apa":"Ori, A., Toyama, B. H., Harris, M. S., Bock, T., Iskar, M., Bork, P., … Beck, M. (2015). Integrated transcriptome and proteome analyses reveal organ-specific proteome deterioration in old rats. <i>Cell Systems</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.cels.2015.08.012\">https://doi.org/10.1016/j.cels.2015.08.012</a>"},"year":"2015","intvolume":"         1","status":"public","date_created":"2022-04-07T07:49:39Z","month":"09","issue":"3","volume":1,"publisher":"Elsevier","article_type":"original"}]