---
_id: '14551'
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.
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.
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Amy
  full_name: Briffa, Amy
  last_name: Briffa
- first_name: Elizabeth
  full_name: Hollwey, Elizabeth
  id: b8c4f54b-e484-11eb-8fdc-a54df64ef6dd
  last_name: Hollwey
- first_name: Zaigham
  full_name: Shahzad, Zaigham
  last_name: Shahzad
- first_name: Jonathan D.
  full_name: Moore, Jonathan D.
  last_name: Moore
- first_name: David B.
  full_name: Lyons, David B.
  last_name: Lyons
- first_name: Martin
  full_name: Howard, Martin
  last_name: Howard
- first_name: Daniel
  full_name: Zilberman, Daniel
  id: 6973db13-dd5f-11ea-814e-b3e5455e9ed1
  last_name: Zilberman
  orcid: 0000-0002-0123-8649
citation:
  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>
  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>
  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>.
  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.
  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.
  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>.
  short: A. Briffa, E. Hollwey, Z. Shahzad, J.D. Moore, D.B. Lyons, M. Howard, D.
    Zilberman, Cell Systems 14 (2023) 953–967.
date_created: 2023-11-19T23:00:54Z
date_published: 2023-11-15T00:00:00Z
date_updated: 2023-11-20T11:24:34Z
day: '15'
ddc:
- '570'
department:
- _id: DaZi
doi: 10.1016/j.cels.2023.10.007
ec_funded: 1
external_id:
  pmid:
  - '37944515'
file:
- access_level: open_access
  checksum: 101fdac59e6f1102d68ef91f2b5bd51a
  content_type: application/pdf
  creator: dernst
  date_created: 2023-11-20T11:22:52Z
  date_updated: 2023-11-20T11:22:52Z
  file_id: '14580'
  file_name: 2023_CellSystems_Briffa.pdf
  file_size: 5587897
  relation: main_file
  success: 1
file_date_updated: 2023-11-20T11:22:52Z
has_accepted_license: '1'
intvolume: '        14'
issue: '11'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '11'
oa: 1
oa_version: Published Version
page: 953-967
pmid: 1
project:
- _id: 62935a00-2b32-11ec-9570-eff30fa39068
  call_identifier: H2020
  grant_number: '725746'
  name: Quantitative analysis of DNA methylation maintenance with chromatin
publication: Cell Systems
publication_identifier:
  eissn:
  - 2405-4720
  issn:
  - 2405-4712
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: Millennia-long epigenetic fluctuations generate intragenic DNA methylation
  variance in Arabidopsis populations
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 14
year: '2023'
...
---
_id: '11449'
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.
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.
article_processing_charge: No
article_type: original
author:
- first_name: Donovan J.
  full_name: Anderson, Donovan J.
  last_name: Anderson
- first_name: Florian
  full_name: Pauler, Florian
  id: 48EA0138-F248-11E8-B48F-1D18A9856A87
  last_name: Pauler
- first_name: Aaron
  full_name: Mckenna, Aaron
  last_name: Mckenna
- first_name: Jay
  full_name: Shendure, Jay
  last_name: Shendure
- first_name: Simon
  full_name: Hippenmeyer, Simon
  id: 37B36620-F248-11E8-B48F-1D18A9856A87
  last_name: Hippenmeyer
  orcid: 0000-0003-2279-1061
- first_name: Marshall S.
  full_name: Horwitz, Marshall S.
  last_name: Horwitz
citation:
  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>
  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>
  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>.
  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.
  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.
  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>.
  short: D.J. Anderson, F. Pauler, A. Mckenna, J. Shendure, S. Hippenmeyer, M.S. Horwitz,
    Cell Systems 13 (2022) 438–453.e5.
date_created: 2022-06-19T22:01:57Z
date_published: 2022-06-15T00:00:00Z
date_updated: 2023-08-03T07:19:43Z
day: '15'
department:
- _id: SiHi
doi: 10.1016/j.cels.2022.03.006
ec_funded: 1
external_id:
  isi:
  - '000814124400002'
  pmid:
  - '35452605'
intvolume: '        13'
isi: 1
issue: '6'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.1016/j.cels.2022.03.006
month: '06'
oa: 1
oa_version: Published Version
page: 438-453.e5
pmid: 1
project:
- _id: 260018B0-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '725780'
  name: Principles of Neural Stem Cell Lineage Progression in Cerebral Cortex Development
- _id: 25D92700-B435-11E9-9278-68D0E5697425
  grant_number: LS13-002
  name: Mapping Cell-Type Specificity of the Genomic Imprintome in the Brain
publication: Cell Systems
publication_identifier:
  eissn:
  - 2405-4720
  issn:
  - 2405-4712
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: Simultaneous brain cell type and lineage determined by scRNA-seq reveals stereotyped
  cortical development
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 13
year: '2022'
...
---
_id: '7026'
abstract:
- lang: eng
  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.
acknowledged_ssus:
- _id: LifeSc
article_processing_charge: No
article_type: original
author:
- first_name: Martin
  full_name: Lukacisin, Martin
  id: 298FFE8C-F248-11E8-B48F-1D18A9856A87
  last_name: Lukacisin
  orcid: 0000-0001-6549-4177
- first_name: Tobias
  full_name: Bollenbach, Tobias
  id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
  last_name: Bollenbach
  orcid: 0000-0003-4398-476X
citation:
  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>
  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>
  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>.
  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.
  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.
  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>.
  short: M. Lukacisin, M.T. Bollenbach, Cell Systems 9 (2019) 423-433.e1-e3.
date_created: 2019-11-15T10:51:42Z
date_published: 2019-11-27T00:00:00Z
date_updated: 2023-08-30T07:24:58Z
day: '27'
ddc:
- '570'
department:
- _id: ToBo
doi: 10.1016/j.cels.2019.10.004
external_id:
  isi:
  - '000499495400003'
file:
- access_level: open_access
  checksum: 7a11d6c2f9523d65b049512d61733178
  content_type: application/pdf
  creator: dernst
  date_created: 2019-11-15T10:57:42Z
  date_updated: 2020-07-14T12:47:48Z
  file_id: '7027'
  file_name: 2019_CellSystems_Lukacisin.pdf
  file_size: 4238460
  relation: main_file
file_date_updated: 2020-07-14T12:47:48Z
has_accepted_license: '1'
intvolume: '         9'
isi: 1
issue: '5'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
page: 423-433.e1-e3
project:
- _id: 25E9AF9E-B435-11E9-9278-68D0E5697425
  call_identifier: FWF
  grant_number: P27201-B22
  name: Revealing the mechanisms underlying drug interactions
- _id: 25EB3A80-B435-11E9-9278-68D0E5697425
  grant_number: RGP0042/2013
  name: Revealing the fundamental limits of cell growth
publication: Cell Systems
publication_identifier:
  issn:
  - 2405-4712
publication_status: published
publisher: Cell Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Emergent gene expression responses to drug combinations predict higher-order
  drug interactions
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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 9
year: '2019'
...
---
_id: '11078'
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.
article_processing_charge: No
article_type: original
author:
- first_name: Alessandro
  full_name: Ori, Alessandro
  last_name: Ori
- first_name: Brandon H.
  full_name: Toyama, Brandon H.
  last_name: Toyama
- first_name: Michael S.
  full_name: Harris, Michael S.
  last_name: Harris
- first_name: Thomas
  full_name: Bock, Thomas
  last_name: Bock
- first_name: Murat
  full_name: Iskar, Murat
  last_name: Iskar
- first_name: Peer
  full_name: Bork, Peer
  last_name: Bork
- first_name: Nicholas T.
  full_name: Ingolia, Nicholas T.
  last_name: Ingolia
- first_name: Martin W
  full_name: HETZER, Martin W
  id: 86c0d31b-b4eb-11ec-ac5a-eae7b2e135ed
  last_name: HETZER
  orcid: 0000-0002-2111-992X
- first_name: Martin
  full_name: Beck, Martin
  last_name: Beck
citation:
  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>
  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>
  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>.
  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.
  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.
  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>.
  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.
date_created: 2022-04-07T07:49:39Z
date_published: 2015-09-23T00:00:00Z
date_updated: 2022-07-18T08:44:07Z
day: '23'
doi: 10.1016/j.cels.2015.08.012
extern: '1'
external_id:
  pmid:
  - '27135913'
intvolume: '         1'
issue: '3'
keyword:
- Cell Biology
- Histology
- Pathology and Forensic Medicine
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.1016/j.cels.2015.08.012
month: '09'
oa: 1
oa_version: Published Version
page: P224-237
pmid: 1
publication: Cell Systems
publication_identifier:
  issn:
  - 2405-4712
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: Integrated transcriptome and proteome analyses reveal organ-specific proteome
  deterioration in old rats
type: journal_article
user_id: 72615eeb-f1f3-11ec-aa25-d4573ddc34fd
volume: 1
year: '2015'
...