---
_id: '315'
abstract:
- lang: eng
  text: 'More than 100 years after Grigg’s influential analysis of species’ borders,
    the causes of limits to species’ ranges still represent a puzzle that has never
    been understood with clarity. The topic has become especially important recently
    as many scientists have become interested in the potential for species’ ranges
    to shift in response to climate change—and yet nearly all of those studies fail
    to recognise or incorporate evolutionary genetics in a way that relates to theoretical
    developments. I show that range margins can be understood based on just two measurable
    parameters: (i) the fitness cost of dispersal—a measure of environmental heterogeneity—and
    (ii) the strength of genetic drift, which reduces genetic diversity. Together,
    these two parameters define an ‘expansion threshold’: adaptation fails when genetic
    drift reduces genetic diversity below that required for adaptation to a heterogeneous
    environment. When the key parameters drop below this expansion threshold locally,
    a sharp range margin forms. When they drop below this threshold throughout the
    species’ range, adaptation collapses everywhere, resulting in either extinction
    or formation of a fragmented metapopulation. Because the effects of dispersal
    differ fundamentally with dimension, the second parameter—the strength of genetic
    drift—is qualitatively different compared to a linear habitat. In two-dimensional
    habitats, genetic drift becomes effectively independent of selection. It decreases
    with ‘neighbourhood size’—the number of individuals accessible by dispersal within
    one generation. Moreover, in contrast to earlier predictions, which neglected
    evolution of genetic variance and/or stochasticity in two dimensions, dispersal
    into small marginal populations aids adaptation. This is because the reduction
    of both genetic and demographic stochasticity has a stronger effect than the cost
    of dispersal through increased maladaptation. The expansion threshold thus provides
    a novel, theoretically justified, and testable prediction for formation of the
    range margin and collapse of the species’ range.'
article_number: e2005372
article_processing_charge: No
author:
- first_name: Jitka
  full_name: Polechova, Jitka
  id: 3BBFB084-F248-11E8-B48F-1D18A9856A87
  last_name: Polechova
  orcid: 0000-0003-0951-3112
citation:
  ama: Polechova J. Is the sky the limit? On the expansion threshold of a species’
    range. <i>PLoS Biology</i>. 2018;16(6). doi:<a href="https://doi.org/10.1371/journal.pbio.2005372">10.1371/journal.pbio.2005372</a>
  apa: Polechova, J. (2018). Is the sky the limit? On the expansion threshold of a
    species’ range. <i>PLoS Biology</i>. Public Library of Science. <a href="https://doi.org/10.1371/journal.pbio.2005372">https://doi.org/10.1371/journal.pbio.2005372</a>
  chicago: Polechova, Jitka. “Is the Sky the Limit? On the Expansion Threshold of
    a Species’ Range.” <i>PLoS Biology</i>. Public Library of Science, 2018. <a href="https://doi.org/10.1371/journal.pbio.2005372">https://doi.org/10.1371/journal.pbio.2005372</a>.
  ieee: J. Polechova, “Is the sky the limit? On the expansion threshold of a species’
    range,” <i>PLoS Biology</i>, vol. 16, no. 6. Public Library of Science, 2018.
  ista: Polechova J. 2018. Is the sky the limit? On the expansion threshold of a species’
    range. PLoS Biology. 16(6), e2005372.
  mla: Polechova, Jitka. “Is the Sky the Limit? On the Expansion Threshold of a Species’
    Range.” <i>PLoS Biology</i>, vol. 16, no. 6, e2005372, Public Library of Science,
    2018, doi:<a href="https://doi.org/10.1371/journal.pbio.2005372">10.1371/journal.pbio.2005372</a>.
  short: J. Polechova, PLoS Biology 16 (2018).
date_created: 2018-12-11T11:45:46Z
date_published: 2018-06-15T00:00:00Z
date_updated: 2025-07-10T11:52:27Z
day: '15'
ddc:
- '576'
department:
- _id: NiBa
doi: 10.1371/journal.pbio.2005372
file:
- access_level: open_access
  checksum: 908c52751bba30c55ed36789e5e4c84d
  content_type: application/pdf
  creator: dernst
  date_created: 2019-01-22T08:30:03Z
  date_updated: 2020-07-14T12:46:01Z
  file_id: '5870'
  file_name: 2017_PLOS_Polechova.pdf
  file_size: 6968201
  relation: main_file
file_date_updated: 2020-07-14T12:46:01Z
has_accepted_license: '1'
intvolume: '        16'
issue: '6'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
publication: PLoS Biology
publication_identifier:
  issn:
  - 1544-9173
publication_status: published
publisher: Public Library of Science
publist_id: '7550'
quality_controlled: '1'
related_material:
  record:
  - id: '9839'
    relation: research_data
    status: public
scopus_import: '1'
status: public
title: Is the sky the limit? On the expansion threshold of a species’ range
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: 16
year: '2018'
...
---
_id: '316'
abstract:
- lang: eng
  text: 'Self-incompatibility (SI) is a genetically based recognition system that
    functions to prevent self-fertilization and mating among related plants. An enduring
    puzzle in SI is how the high diversity observed in nature arises and is maintained.
    Based on the underlying recognition mechanism, SI can be classified into two main
    groups: self- and non-self recognition. Most work has focused on diversification
    within self-recognition systems despite expected differences between the two groups
    in the evolutionary pathways and outcomes of diversification. Here, we use a deterministic
    population genetic model and stochastic simulations to investigate how novel S-haplotypes
    evolve in a gametophytic non-self recognition (SRNase/S Locus F-box (SLF)) SI
    system. For this model the pathways for diversification involve either the maintenance
    or breakdown of SI and can vary in the order of mutations of the female (SRNase)
    and male (SLF) components. We show analytically that diversification can occur
    with high inbreeding depression and self-pollination, but this varies with evolutionary
    pathway and level of completeness (which determines the number of potential mating
    partners in the population), and in general is more likely for lower haplotype
    number. The conditions for diversification are broader in stochastic simulations
    of finite population size. However, the number of haplotypes observed under high
    inbreeding and moderate to high self-pollination is less than that commonly observed
    in nature. Diversification was observed through pathways that maintain SI as well
    as through self-compatible intermediates. Yet the lifespan of diversified haplotypes
    was sensitive to their level of completeness. By examining diversification in
    a non-self recognition SI system, this model extends our understanding of the
    evolution and maintenance of haplotype diversity observed in a self recognition
    system common in flowering plants.'
article_processing_charge: No
article_type: original
author:
- first_name: Katarina
  full_name: Bodova, Katarina
  id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87
  last_name: Bodova
  orcid: 0000-0002-7214-0171
- first_name: Tadeas
  full_name: Priklopil, Tadeas
  id: 3C869AA0-F248-11E8-B48F-1D18A9856A87
  last_name: Priklopil
- first_name: David
  full_name: Field, David
  id: 419049E2-F248-11E8-B48F-1D18A9856A87
  last_name: Field
  orcid: 0000-0002-4014-8478
- first_name: Nicholas H
  full_name: Barton, Nicholas H
  id: 4880FE40-F248-11E8-B48F-1D18A9856A87
  last_name: Barton
  orcid: 0000-0002-8548-5240
- first_name: Melinda
  full_name: Pickup, Melinda
  id: 2C78037E-F248-11E8-B48F-1D18A9856A87
  last_name: Pickup
  orcid: 0000-0001-6118-0541
citation:
  ama: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. Evolutionary pathways
    for the generation of new self-incompatibility haplotypes in a non-self recognition
    system. <i>Genetics</i>. 2018;209(3):861-883. doi:<a href="https://doi.org/10.1534/genetics.118.300748">10.1534/genetics.118.300748</a>
  apa: Bodova, K., Priklopil, T., Field, D., Barton, N. H., &#38; Pickup, M. (2018).
    Evolutionary pathways for the generation of new self-incompatibility haplotypes
    in a non-self recognition system. <i>Genetics</i>. Genetics Society of America.
    <a href="https://doi.org/10.1534/genetics.118.300748">https://doi.org/10.1534/genetics.118.300748</a>
  chicago: Bodova, Katarina, Tadeas Priklopil, David Field, Nicholas H Barton, and
    Melinda Pickup. “Evolutionary Pathways for the Generation of New Self-Incompatibility
    Haplotypes in a Non-Self Recognition System.” <i>Genetics</i>. Genetics Society
    of America, 2018. <a href="https://doi.org/10.1534/genetics.118.300748">https://doi.org/10.1534/genetics.118.300748</a>.
  ieee: K. Bodova, T. Priklopil, D. Field, N. H. Barton, and M. Pickup, “Evolutionary
    pathways for the generation of new self-incompatibility haplotypes in a non-self
    recognition system,” <i>Genetics</i>, vol. 209, no. 3. Genetics Society of America,
    pp. 861–883, 2018.
  ista: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. 2018. Evolutionary pathways
    for the generation of new self-incompatibility haplotypes in a non-self recognition
    system. Genetics. 209(3), 861–883.
  mla: Bodova, Katarina, et al. “Evolutionary Pathways for the Generation of New Self-Incompatibility
    Haplotypes in a Non-Self Recognition System.” <i>Genetics</i>, vol. 209, no. 3,
    Genetics Society of America, 2018, pp. 861–83, doi:<a href="https://doi.org/10.1534/genetics.118.300748">10.1534/genetics.118.300748</a>.
  short: K. Bodova, T. Priklopil, D. Field, N.H. Barton, M. Pickup, Genetics 209 (2018)
    861–883.
date_created: 2018-12-11T11:45:47Z
date_published: 2018-07-01T00:00:00Z
date_updated: 2025-04-15T06:50:00Z
day: '01'
department:
- _id: NiBa
- _id: GaTk
doi: 10.1534/genetics.118.300748
ec_funded: 1
external_id:
  isi:
  - '000437171700017'
intvolume: '       209'
isi: 1
issue: '3'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.biorxiv.org/node/80098.abstract
month: '07'
oa: 1
oa_version: Preprint
page: 861-883
project:
- _id: 25B36484-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '329960'
  name: Mating system and the evolutionary dynamics of hybrid zones
- _id: 25B07788-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '250152'
  name: Limits to selection in biology and in evolutionary computation
- _id: 25681D80-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '291734'
  name: International IST Postdoc Fellowship Programme
publication: Genetics
publication_status: published
publisher: Genetics Society of America
quality_controlled: '1'
related_material:
  link:
  - description: News on IST Homepage
    relation: press_release
    url: https://ist.ac.at/en/news/recognizing-others-but-not-yourself-new-insights-into-the-evolution-of-plant-mating/
  record:
  - id: '9813'
    relation: research_data
    status: public
scopus_import: '1'
status: public
title: Evolutionary pathways for the generation of new self-incompatibility haplotypes
  in a non-self recognition system
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 209
year: '2018'
...
---
_id: '33'
abstract:
- lang: eng
  text: Secondary contact is the reestablishment of gene flow between sister populations
    that have diverged. For instance, at the end of the Quaternary glaciations in
    Europe, secondary contact occurred during the northward expansion of the populations
    which had found refugia in the southern peninsulas. With the advent of multi-locus
    markers, secondary contact can be investigated using various molecular signatures
    including gradients of allele frequency, admixture clines, and local increase
    of genetic differentiation. We use coalescent simulations to investigate if molecular
    data provide enough information to distinguish between secondary contact following
    range expansion and an alternative evolutionary scenario consisting of a barrier
    to gene flow in an isolation-by-distance model. We find that an excess of linkage
    disequilibrium and of genetic diversity at the suture zone is a unique signature
    of secondary contact. We also find that the directionality index ψ, which was
    proposed to study range expansion, is informative to distinguish between the two
    hypotheses. However, although evidence for secondary contact is usually conveyed
    by statistics related to admixture coefficients, we find that they can be confounded
    by isolation-by-distance. We recommend to account for the spatial repartition
    of individuals when investigating secondary contact in order to better reflect
    the complex spatio-temporal evolution of populations and species.
acknowledgement: 'Johanna Bertl was supported by the Vienna Graduate School of Population
  Genetics (Austrian Science Fund (FWF): W1225-B20) and worked on this project while
  employed at the Department of Statistics and Operations Research, University of
  Vienna, Austria. This article was developed in the framework of the Grenoble Alpes
  Data Institute, which is supported by the French National Research Agency under
  the “Investissments d’avenir” program (ANR-15-IDEX-02).'
article_number: e5325
article_processing_charge: No
author:
- first_name: Johanna
  full_name: Bertl, Johanna
  last_name: Bertl
- first_name: Harald
  full_name: Ringbauer, Harald
  id: 417FCFF4-F248-11E8-B48F-1D18A9856A87
  last_name: Ringbauer
  orcid: 0000-0002-4884-9682
- first_name: Michaël
  full_name: Blum, Michaël
  last_name: Blum
citation:
  ama: Bertl J, Ringbauer H, Blum M. Can secondary contact following range expansion
    be distinguished from barriers to gene flow? <i>PeerJ</i>. 2018;2018(10). doi:<a
    href="https://doi.org/10.7717/peerj.5325">10.7717/peerj.5325</a>
  apa: Bertl, J., Ringbauer, H., &#38; Blum, M. (2018). Can secondary contact following
    range expansion be distinguished from barriers to gene flow? <i>PeerJ</i>. PeerJ.
    <a href="https://doi.org/10.7717/peerj.5325">https://doi.org/10.7717/peerj.5325</a>
  chicago: Bertl, Johanna, Harald Ringbauer, and Michaël Blum. “Can Secondary Contact
    Following Range Expansion Be Distinguished from Barriers to Gene Flow?” <i>PeerJ</i>.
    PeerJ, 2018. <a href="https://doi.org/10.7717/peerj.5325">https://doi.org/10.7717/peerj.5325</a>.
  ieee: J. Bertl, H. Ringbauer, and M. Blum, “Can secondary contact following range
    expansion be distinguished from barriers to gene flow?,” <i>PeerJ</i>, vol. 2018,
    no. 10. PeerJ, 2018.
  ista: Bertl J, Ringbauer H, Blum M. 2018. Can secondary contact following range
    expansion be distinguished from barriers to gene flow? PeerJ. 2018(10), e5325.
  mla: Bertl, Johanna, et al. “Can Secondary Contact Following Range Expansion Be
    Distinguished from Barriers to Gene Flow?” <i>PeerJ</i>, vol. 2018, no. 10, e5325,
    PeerJ, 2018, doi:<a href="https://doi.org/10.7717/peerj.5325">10.7717/peerj.5325</a>.
  short: J. Bertl, H. Ringbauer, M. Blum, PeerJ 2018 (2018).
date_created: 2018-12-11T11:44:16Z
date_published: 2018-10-01T00:00:00Z
date_updated: 2023-10-17T12:24:43Z
day: '01'
ddc:
- '576'
department:
- _id: NiBa
doi: 10.7717/peerj.5325
external_id:
  isi:
  - '000447204400001'
  pmid:
  - '30294507'
file:
- access_level: open_access
  checksum: 3334886c4b39678db4c4b74299ca14ba
  content_type: application/pdf
  creator: dernst
  date_created: 2018-12-17T10:46:06Z
  date_updated: 2020-07-14T12:46:06Z
  file_id: '5692'
  file_name: 2018_PeerJ_Bertl.pdf
  file_size: 1328344
  relation: main_file
file_date_updated: 2020-07-14T12:46:06Z
has_accepted_license: '1'
intvolume: '      2018'
isi: 1
issue: '10'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
pmid: 1
publication: PeerJ
publication_status: published
publisher: PeerJ
publist_id: '8022'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Can secondary contact following range expansion be distinguished from barriers
  to gene flow?
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: 2018
year: '2018'
...
---
_id: '38'
abstract:
- lang: eng
  text: 'Genomes of closely-related species or populations often display localized
    regions of enhanced relative sequence divergence, termed genomic islands. It has
    been proposed that these islands arise through selective sweeps and/or barriers
    to gene flow. Here, we genetically dissect a genomic island that controls flower
    color pattern differences between two subspecies of Antirrhinum majus, A.m.striatum
    and A.m.pseudomajus, and relate it to clinal variation across a natural hybrid
    zone. We show that selective sweeps likely raised relative divergence at two tightly-linked
    MYB-like transcription factors, leading to distinct flower patterns in the two
    subspecies. The two patterns provide alternate floral guides and create a strong
    barrier to gene flow where populations come into contact. This barrier affects
    the selected flower color genes and tightlylinked loci, but does not extend outside
    of this domain, allowing gene flow to lower relative divergence for the rest of
    the chromosome. Thus, both selective sweeps and barriers to gene flow play a role
    in shaping genomic islands: sweeps cause elevation in relative divergence, while
    heterogeneous gene flow flattens the surrounding "sea," making the island of divergence
    stand out. By showing how selective sweeps establish alternative adaptive phenotypes
    that lead to barriers to gene flow, our study sheds light on possible mechanisms
    leading to reproductive isolation and speciation.'
acknowledgement: ' ERC Grant 201252 (to N.H.B.)'
article_processing_charge: No
author:
- first_name: Hugo
  full_name: Tavares, Hugo
  last_name: Tavares
- first_name: Annabel
  full_name: Whitley, Annabel
  last_name: Whitley
- first_name: David
  full_name: Field, David
  id: 419049E2-F248-11E8-B48F-1D18A9856A87
  last_name: Field
  orcid: 0000-0002-4014-8478
- first_name: Desmond
  full_name: Bradley, Desmond
  last_name: Bradley
- first_name: Matthew
  full_name: Couchman, Matthew
  last_name: Couchman
- first_name: Lucy
  full_name: Copsey, Lucy
  last_name: Copsey
- first_name: Joane
  full_name: Elleouet, Joane
  last_name: Elleouet
- first_name: Monique
  full_name: Burrus, Monique
  last_name: Burrus
- first_name: Christophe
  full_name: Andalo, Christophe
  last_name: Andalo
- first_name: Miaomiao
  full_name: Li, Miaomiao
  last_name: Li
- first_name: Qun
  full_name: Li, Qun
  last_name: Li
- first_name: Yongbiao
  full_name: Xue, Yongbiao
  last_name: Xue
- first_name: Alexandra B
  full_name: Rebocho, Alexandra B
  last_name: Rebocho
- first_name: Nicholas H
  full_name: Barton, Nicholas H
  id: 4880FE40-F248-11E8-B48F-1D18A9856A87
  last_name: Barton
  orcid: 0000-0002-8548-5240
- first_name: Enrico
  full_name: Coen, Enrico
  last_name: Coen
citation:
  ama: Tavares H, Whitley A, Field D, et al. Selection and gene flow shape genomic
    islands that control floral guides. <i>PNAS</i>. 2018;115(43):11006-11011. doi:<a
    href="https://doi.org/10.1073/pnas.1801832115">10.1073/pnas.1801832115</a>
  apa: Tavares, H., Whitley, A., Field, D., Bradley, D., Couchman, M., Copsey, L.,
    … Coen, E. (2018). Selection and gene flow shape genomic islands that control
    floral guides. <i>PNAS</i>. National Academy of Sciences. <a href="https://doi.org/10.1073/pnas.1801832115">https://doi.org/10.1073/pnas.1801832115</a>
  chicago: Tavares, Hugo, Annabel Whitley, David Field, Desmond Bradley, Matthew Couchman,
    Lucy Copsey, Joane Elleouet, et al. “Selection and Gene Flow Shape Genomic Islands
    That Control Floral Guides.” <i>PNAS</i>. National Academy of Sciences, 2018.
    <a href="https://doi.org/10.1073/pnas.1801832115">https://doi.org/10.1073/pnas.1801832115</a>.
  ieee: H. Tavares <i>et al.</i>, “Selection and gene flow shape genomic islands that
    control floral guides,” <i>PNAS</i>, vol. 115, no. 43. National Academy of Sciences,
    pp. 11006–11011, 2018.
  ista: Tavares H, Whitley A, Field D, Bradley D, Couchman M, Copsey L, Elleouet J,
    Burrus M, Andalo C, Li M, Li Q, Xue Y, Rebocho AB, Barton NH, Coen E. 2018. Selection
    and gene flow shape genomic islands that control floral guides. PNAS. 115(43),
    11006–11011.
  mla: Tavares, Hugo, et al. “Selection and Gene Flow Shape Genomic Islands That Control
    Floral Guides.” <i>PNAS</i>, vol. 115, no. 43, National Academy of Sciences, 2018,
    pp. 11006–11, doi:<a href="https://doi.org/10.1073/pnas.1801832115">10.1073/pnas.1801832115</a>.
  short: H. Tavares, A. Whitley, D. Field, D. Bradley, M. Couchman, L. Copsey, J.
    Elleouet, M. Burrus, C. Andalo, M. Li, Q. Li, Y. Xue, A.B. Rebocho, N.H. Barton,
    E. Coen, PNAS 115 (2018) 11006–11011.
date_created: 2018-12-11T11:44:18Z
date_published: 2018-10-23T00:00:00Z
date_updated: 2025-07-10T11:52:32Z
day: '23'
ddc:
- '570'
department:
- _id: NiBa
doi: 10.1073/pnas.1801832115
external_id:
  isi:
  - '000448040500065'
  pmid:
  - '30297406'
file:
- access_level: open_access
  checksum: d2305d0cc81dbbe4c1c677d64ad6f6d1
  content_type: application/pdf
  creator: dernst
  date_created: 2018-12-17T08:44:03Z
  date_updated: 2020-07-14T12:46:16Z
  file_id: '5683'
  file_name: 11006.full.pdf
  file_size: 1911302
  relation: main_file
file_date_updated: 2020-07-14T12:46:16Z
has_accepted_license: '1'
intvolume: '       115'
isi: 1
issue: '43'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
month: '10'
oa: 1
oa_version: Published Version
page: 11006 - 11011
pmid: 1
publication: PNAS
publication_identifier:
  issn:
  - 0027-8424
publication_status: published
publisher: National Academy of Sciences
publist_id: '8017'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Selection and gene flow shape genomic islands that control floral guides
tmp:
  image: /images/cc_by_nc_nd.png
  legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
  name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
    (CC BY-NC-ND 4.0)
  short: CC BY-NC-ND (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 115
year: '2018'
...
---
_id: '39'
abstract:
- lang: eng
  text: We study how a block of genome with a large number of weakly selected loci
    introgresses under directional selection into a genetically homogeneous population.
    We derive exact expressions for the expected rate of growth of any fragment of
    the introduced block during the initial phase of introgression, and show that
    the growth rate of a single-locus variant is largely insensitive to its own additive
    effect, but depends instead on the combined effect of all loci within a characteristic
    linkage scale. The expected growth rate of a fragment is highly correlated with
    its long-term introgression probability in populations of moderate size, and can
    hence identify variants that are likely to introgress across replicate populations.
    We clarify how the introgression probability of an individual variant is determined
    by the interplay between hitchhiking with relatively large fragments during the
    early phase of introgression and selection on fine-scale variation within these,
    which at longer times results in differential introgression probabilities for
    beneficial and deleterious loci within successful fragments. By simulating individuals,
    we also investigate how introgression probabilities at individual loci depend
    on the variance of fitness effects, the net fitness of the introduced block, and
    the size of the recipient population, and how this shapes the net advance under
    selection. Our work suggests that even highly replicable substitutions may be
    associated with a range of selective effects, which makes it challenging to fine
    map the causal loci that underlie polygenic adaptation.
article_processing_charge: No
article_type: original
author:
- first_name: Himani
  full_name: Sachdeva, Himani
  id: 42377A0A-F248-11E8-B48F-1D18A9856A87
  last_name: Sachdeva
- first_name: Nicholas H
  full_name: Barton, Nicholas H
  id: 4880FE40-F248-11E8-B48F-1D18A9856A87
  last_name: Barton
  orcid: 0000-0002-8548-5240
citation:
  ama: Sachdeva H, Barton NH. Replicability of introgression under linked, polygenic
    selection. <i>Genetics</i>. 2018;210(4):1411-1427. doi:<a href="https://doi.org/10.1534/genetics.118.301429">10.1534/genetics.118.301429</a>
  apa: Sachdeva, H., &#38; Barton, N. H. (2018). Replicability of introgression under
    linked, polygenic selection. <i>Genetics</i>. Genetics Society of America. <a
    href="https://doi.org/10.1534/genetics.118.301429">https://doi.org/10.1534/genetics.118.301429</a>
  chicago: Sachdeva, Himani, and Nicholas H Barton. “Replicability of Introgression
    under Linked, Polygenic Selection.” <i>Genetics</i>. Genetics Society of America,
    2018. <a href="https://doi.org/10.1534/genetics.118.301429">https://doi.org/10.1534/genetics.118.301429</a>.
  ieee: H. Sachdeva and N. H. Barton, “Replicability of introgression under linked,
    polygenic selection,” <i>Genetics</i>, vol. 210, no. 4. Genetics Society of America,
    pp. 1411–1427, 2018.
  ista: Sachdeva H, Barton NH. 2018. Replicability of introgression under linked,
    polygenic selection. Genetics. 210(4), 1411–1427.
  mla: Sachdeva, Himani, and Nicholas H. Barton. “Replicability of Introgression under
    Linked, Polygenic Selection.” <i>Genetics</i>, vol. 210, no. 4, Genetics Society
    of America, 2018, pp. 1411–27, doi:<a href="https://doi.org/10.1534/genetics.118.301429">10.1534/genetics.118.301429</a>.
  short: H. Sachdeva, N.H. Barton, Genetics 210 (2018) 1411–1427.
date_created: 2018-12-11T11:44:18Z
date_published: 2018-12-04T00:00:00Z
date_updated: 2025-07-10T11:52:33Z
day: '04'
department:
- _id: NiBa
doi: 10.1534/genetics.118.301429
external_id:
  isi:
  - '000452315900021'
intvolume: '       210'
isi: 1
issue: '4'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.biorxiv.org/content/10.1101/379578v1
month: '12'
oa: 1
oa_version: Preprint
page: 1411-1427
publication: Genetics
publication_identifier:
  issn:
  - 0016-6731
publication_status: published
publisher: Genetics Society of America
quality_controlled: '1'
scopus_import: '1'
status: public
title: Replicability of introgression under linked, polygenic selection
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 210
year: '2018'
...
---
_id: '40'
abstract:
- lang: eng
  text: Hanemaaijer et al. (Molecular Ecology, 27, 2018) describe the genetic consequences
    of the introgression of an insecticide resistance allele into a mosquito population.
    Linked alleles initially increased, but many of these later declined. It is hard
    to determine whether this decline was due to counter‐selection, rather than simply
    to chance.
article_processing_charge: Yes (via OA deal)
article_type: letter_note
author:
- first_name: Nicholas H
  full_name: Barton, Nicholas H
  id: 4880FE40-F248-11E8-B48F-1D18A9856A87
  last_name: Barton
  orcid: 0000-0002-8548-5240
citation:
  ama: Barton NH. The consequences of an introgression event. <i>Molecular Ecology</i>.
    2018;27(24):4973-4975. doi:<a href="https://doi.org/10.1111/mec.14950">10.1111/mec.14950</a>
  apa: Barton, N. H. (2018). The consequences of an introgression event. <i>Molecular
    Ecology</i>. Wiley. <a href="https://doi.org/10.1111/mec.14950">https://doi.org/10.1111/mec.14950</a>
  chicago: Barton, Nicholas H. “The Consequences of an Introgression Event.” <i>Molecular
    Ecology</i>. Wiley, 2018. <a href="https://doi.org/10.1111/mec.14950">https://doi.org/10.1111/mec.14950</a>.
  ieee: N. H. Barton, “The consequences of an introgression event,” <i>Molecular Ecology</i>,
    vol. 27, no. 24. Wiley, pp. 4973–4975, 2018.
  ista: Barton NH. 2018. The consequences of an introgression event. Molecular Ecology.
    27(24), 4973–4975.
  mla: Barton, Nicholas H. “The Consequences of an Introgression Event.” <i>Molecular
    Ecology</i>, vol. 27, no. 24, Wiley, 2018, pp. 4973–75, doi:<a href="https://doi.org/10.1111/mec.14950">10.1111/mec.14950</a>.
  short: N.H. Barton, Molecular Ecology 27 (2018) 4973–4975.
corr_author: '1'
date_created: 2018-12-11T11:44:18Z
date_published: 2018-12-31T00:00:00Z
date_updated: 2025-07-10T11:52:34Z
day: '31'
ddc:
- '576'
department:
- _id: NiBa
doi: 10.1111/mec.14950
external_id:
  isi:
  - '000454600500001'
  pmid:
  - '30599087'
file:
- access_level: open_access
  content_type: application/pdf
  creator: apreinsp
  date_created: 2019-07-19T06:54:46Z
  date_updated: 2020-07-14T12:46:22Z
  file_id: '6652'
  file_name: 2018_MolecularEcology_BartonNick.pdf
  file_size: 295452
  relation: main_file
file_date_updated: 2020-07-14T12:46:22Z
has_accepted_license: '1'
intvolume: '        27'
isi: 1
issue: '24'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
page: 4973-4975
pmid: 1
publication: Molecular Ecology
publication_identifier:
  issn:
  - 1365-294X
publication_status: published
publisher: Wiley
publist_id: '8014'
quality_controlled: '1'
related_material:
  record:
  - id: '9805'
    relation: research_data
    status: public
scopus_import: '1'
status: public
title: The consequences of an introgression event
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: 27
year: '2018'
...
---
_id: '423'
abstract:
- lang: eng
  text: Herd immunity, a process in which resistant individuals limit the spread of
    a pathogen among susceptible hosts has been extensively studied in eukaryotes.
    Even though bacteria have evolved multiple immune systems against their phage
    pathogens, herd immunity in bacteria remains unexplored. Here we experimentally
    demonstrate that herd immunity arises during phage epidemics in structured and
    unstructured Escherichia coli populations consisting of differing frequencies
    of susceptible and resistant cells harboring CRISPR immunity. In addition, we
    develop a mathematical model that quantifies how herd immunity is affected by
    spatial population structure, bacterial growth rate, and phage replication rate.
    Using our model we infer a general epidemiological rule describing the relative
    speed of an epidemic in partially resistant spatially structured populations.
    Our experimental and theoretical findings indicate that herd immunity may be important
    in bacterial communities, allowing for stable coexistence of bacteria and their
    phages and the maintenance of polymorphism in bacterial immunity.
acknowledgement: "We are grateful to Remy Chait for his help and assistance with establishing
  our experimental setups and to Tobias Bergmiller for valuable insights into some
  specific experimental details. We thank Luciano Marraffini for donating us the pCas9
  plasmid used in this study. We also want to express our gratitude to Seth Barribeau,
  Andrea Betancourt, Călin Guet, Mato Lagator, Tiago Paixão and Maroš Pleška for valuable
  discussions on the manuscript. Finally, we would like to thank the \r\neditors and
  reviewers for their helpful comments and suggestions."
article_number: e32035
article_processing_charge: No
author:
- first_name: Pavel
  full_name: Payne, Pavel
  id: 35F78294-F248-11E8-B48F-1D18A9856A87
  last_name: Payne
  orcid: 0000-0002-2711-9453
- first_name: Lukas
  full_name: Geyrhofer, Lukas
  last_name: Geyrhofer
- first_name: Nicholas H
  full_name: Barton, Nicholas H
  id: 4880FE40-F248-11E8-B48F-1D18A9856A87
  last_name: Barton
  orcid: 0000-0002-8548-5240
- first_name: Jonathan P
  full_name: Bollback, Jonathan P
  id: 2C6FA9CC-F248-11E8-B48F-1D18A9856A87
  last_name: Bollback
  orcid: 0000-0002-4624-4612
citation:
  ama: Payne P, Geyrhofer L, Barton NH, Bollback JP. CRISPR-based herd immunity can
    limit phage epidemics in bacterial populations. <i>eLife</i>. 2018;7. doi:<a href="https://doi.org/10.7554/eLife.32035">10.7554/eLife.32035</a>
  apa: Payne, P., Geyrhofer, L., Barton, N. H., &#38; Bollback, J. P. (2018). CRISPR-based
    herd immunity can limit phage epidemics in bacterial populations. <i>ELife</i>.
    eLife Sciences Publications. <a href="https://doi.org/10.7554/eLife.32035">https://doi.org/10.7554/eLife.32035</a>
  chicago: Payne, Pavel, Lukas Geyrhofer, Nicholas H Barton, and Jonathan P Bollback.
    “CRISPR-Based Herd Immunity Can Limit Phage Epidemics in Bacterial Populations.”
    <i>ELife</i>. eLife Sciences Publications, 2018. <a href="https://doi.org/10.7554/eLife.32035">https://doi.org/10.7554/eLife.32035</a>.
  ieee: P. Payne, L. Geyrhofer, N. H. Barton, and J. P. Bollback, “CRISPR-based herd
    immunity can limit phage epidemics in bacterial populations,” <i>eLife</i>, vol.
    7. eLife Sciences Publications, 2018.
  ista: Payne P, Geyrhofer L, Barton NH, Bollback JP. 2018. CRISPR-based herd immunity
    can limit phage epidemics in bacterial populations. eLife. 7, e32035.
  mla: Payne, Pavel, et al. “CRISPR-Based Herd Immunity Can Limit Phage Epidemics
    in Bacterial Populations.” <i>ELife</i>, vol. 7, e32035, eLife Sciences Publications,
    2018, doi:<a href="https://doi.org/10.7554/eLife.32035">10.7554/eLife.32035</a>.
  short: P. Payne, L. Geyrhofer, N.H. Barton, J.P. Bollback, ELife 7 (2018).
date_created: 2018-12-11T11:46:23Z
date_published: 2018-03-09T00:00:00Z
date_updated: 2025-03-31T16:00:24Z
day: '09'
ddc:
- '576'
department:
- _id: NiBa
- _id: JoBo
doi: 10.7554/eLife.32035
ec_funded: 1
external_id:
  isi:
  - '000431035800001'
file:
- access_level: open_access
  checksum: 447cf6e680bdc3c01062a8737d876569
  content_type: application/pdf
  creator: dernst
  date_created: 2018-12-17T10:36:07Z
  date_updated: 2020-07-14T12:46:25Z
  file_id: '5689'
  file_name: 2018_eLife_Payne.pdf
  file_size: 3533881
  relation: main_file
file_date_updated: 2020-07-14T12:46:25Z
has_accepted_license: '1'
intvolume: '         7'
isi: 1
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
project:
- _id: 2578D616-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '648440'
  name: Selective Barriers to Horizontal Gene Transfer
publication: eLife
publication_status: published
publisher: eLife Sciences Publications
publist_id: '7400'
quality_controlled: '1'
related_material:
  record:
  - id: '9840'
    relation: research_data
    status: public
scopus_import: '1'
status: public
title: CRISPR-based herd immunity can limit phage epidemics in bacterial 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: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 7
year: '2018'
...
---
_id: '430'
abstract:
- lang: eng
  text: In this issue of GENETICS, a new method for detecting natural selection on
    polygenic traits is developed and applied to sev- eral human examples ( Racimo
    et al. 2018 ). By de fi nition, many loci contribute to variation in polygenic
    traits, and a challenge for evolutionary ge neticists has been that these traits
    can evolve by small, nearly undetectable shifts in allele frequencies across each
    of many, typically unknown, loci. Recently, a helpful remedy has arisen. Genome-wide
    associ- ation studies (GWAS) have been illuminating sets of loci that can be interrogated
    jointly for c hanges in allele frequencies. By aggregating small signal s of change
    across many such loci, directional natural selection is now in principle detect-
    able using genetic data, even for highly polygenic traits. This is an exciting
    arena of progress – with these methods, tests can be made for selection associated
    with traits, and we can now study selection in what may be its most prevalent
    mode. The continuing fast pace of GWAS publications suggest there will be many
    more polygenic tests of selection in the near future, as every new GWAS is an
    opportunity for an accom- panying test of polygenic selection. However, it is
    important to be aware of complications th at arise in interpretation, especially
    given that these studies may easily be misinter- preted both in and outside the
    evolutionary genetics commu- nity. Here, we provide context for understanding
    polygenic tests and urge caution regarding how these results are inter- preted
    and reported upon more broadly.
article_processing_charge: No
author:
- first_name: John
  full_name: Novembre, John
  last_name: Novembre
- first_name: Nicholas H
  full_name: Barton, Nicholas H
  id: 4880FE40-F248-11E8-B48F-1D18A9856A87
  last_name: Barton
  orcid: 0000-0002-8548-5240
citation:
  ama: Novembre J, Barton NH. Tread lightly interpreting polygenic tests of selection.
    <i>Genetics</i>. 2018;208(4):1351-1355. doi:<a href="https://doi.org/10.1534/genetics.118.300786">10.1534/genetics.118.300786</a>
  apa: Novembre, J., &#38; Barton, N. H. (2018). Tread lightly interpreting polygenic
    tests of selection. <i>Genetics</i>. Genetics Society of America. <a href="https://doi.org/10.1534/genetics.118.300786">https://doi.org/10.1534/genetics.118.300786</a>
  chicago: Novembre, John, and Nicholas H Barton. “Tread Lightly Interpreting Polygenic
    Tests of Selection.” <i>Genetics</i>. Genetics Society of America, 2018. <a href="https://doi.org/10.1534/genetics.118.300786">https://doi.org/10.1534/genetics.118.300786</a>.
  ieee: J. Novembre and N. H. Barton, “Tread lightly interpreting polygenic tests
    of selection,” <i>Genetics</i>, vol. 208, no. 4. Genetics Society of America,
    pp. 1351–1355, 2018.
  ista: Novembre J, Barton NH. 2018. Tread lightly interpreting polygenic tests of
    selection. Genetics. 208(4), 1351–1355.
  mla: Novembre, John, and Nicholas H. Barton. “Tread Lightly Interpreting Polygenic
    Tests of Selection.” <i>Genetics</i>, vol. 208, no. 4, Genetics Society of America,
    2018, pp. 1351–55, doi:<a href="https://doi.org/10.1534/genetics.118.300786">10.1534/genetics.118.300786</a>.
  short: J. Novembre, N.H. Barton, Genetics 208 (2018) 1351–1355.
date_created: 2018-12-11T11:46:26Z
date_published: 2018-04-01T00:00:00Z
date_updated: 2023-09-19T10:17:30Z
day: '01'
ddc:
- '576'
department:
- _id: NiBa
doi: 10.1534/genetics.118.300786
external_id:
  isi:
  - '000429094400005'
file:
- access_level: open_access
  checksum: 3d838dc285df394376555b794b6a5ad1
  content_type: application/pdf
  creator: system
  date_created: 2018-12-12T10:12:40Z
  date_updated: 2020-07-14T12:46:26Z
  file_id: '4958'
  file_name: IST-2018-1012-v1+1_2018_Barton_Tread.pdf
  file_size: 500129
  relation: main_file
file_date_updated: 2020-07-14T12:46:26Z
has_accepted_license: '1'
intvolume: '       208'
isi: 1
issue: '4'
language:
- iso: eng
month: '04'
oa: 1
oa_version: Published Version
page: 1351 - 1355
publication: Genetics
publication_status: published
publisher: Genetics Society of America
publist_id: '7393'
pubrep_id: '1012'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Tread lightly interpreting polygenic tests of selection
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: 208
year: '2018'
...
---
_id: '9813'
abstract:
- lang: eng
  text: 'File S1 contains figures that clarify the following features: (i) effect
    of population size on the average number/frequency of SI classes, (ii) changes
    in the minimal completeness deficit in time for a single class, and (iii) diversification
    diagrams for all studied pathways, including the summary figure for k = 8. File
    S2 contains the code required for a stochastic simulation of the SLF system with
    an example. This file also includes the output in the form of figures and tables.'
article_processing_charge: No
author:
- first_name: Katarína
  full_name: Bod'ová, Katarína
  id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87
  last_name: Bod'ová
  orcid: 0000-0002-7214-0171
- first_name: Tadeas
  full_name: Priklopil, Tadeas
  id: 3C869AA0-F248-11E8-B48F-1D18A9856A87
  last_name: Priklopil
- first_name: David
  full_name: Field, David
  id: 419049E2-F248-11E8-B48F-1D18A9856A87
  last_name: Field
  orcid: 0000-0002-4014-8478
- first_name: Nicholas H
  full_name: Barton, Nicholas H
  id: 4880FE40-F248-11E8-B48F-1D18A9856A87
  last_name: Barton
  orcid: 0000-0002-8548-5240
- first_name: Melinda
  full_name: Pickup, Melinda
  id: 2C78037E-F248-11E8-B48F-1D18A9856A87
  last_name: Pickup
  orcid: 0000-0001-6118-0541
citation:
  ama: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. Supplemental material
    for Bodova et al., 2018. 2018. doi:<a href="https://doi.org/10.25386/genetics.6148304.v1">10.25386/genetics.6148304.v1</a>
  apa: Bodova, K., Priklopil, T., Field, D., Barton, N. H., &#38; Pickup, M. (2018).
    Supplemental material for Bodova et al., 2018. Genetics Society of America. <a
    href="https://doi.org/10.25386/genetics.6148304.v1">https://doi.org/10.25386/genetics.6148304.v1</a>
  chicago: Bodova, Katarina, Tadeas Priklopil, David Field, Nicholas H Barton, and
    Melinda Pickup. “Supplemental Material for Bodova et Al., 2018.” Genetics Society
    of America, 2018. <a href="https://doi.org/10.25386/genetics.6148304.v1">https://doi.org/10.25386/genetics.6148304.v1</a>.
  ieee: K. Bodova, T. Priklopil, D. Field, N. H. Barton, and M. Pickup, “Supplemental
    material for Bodova et al., 2018.” Genetics Society of America, 2018.
  ista: Bodova K, Priklopil T, Field D, Barton NH, Pickup M. 2018. Supplemental material
    for Bodova et al., 2018, Genetics Society of America, <a href="https://doi.org/10.25386/genetics.6148304.v1">10.25386/genetics.6148304.v1</a>.
  mla: Bodova, Katarina, et al. <i>Supplemental Material for Bodova et Al., 2018</i>.
    Genetics Society of America, 2018, doi:<a href="https://doi.org/10.25386/genetics.6148304.v1">10.25386/genetics.6148304.v1</a>.
  short: K. Bodova, T. Priklopil, D. Field, N.H. Barton, M. Pickup, (2018).
date_created: 2021-08-06T13:04:32Z
date_published: 2018-04-30T00:00:00Z
date_updated: 2025-04-15T07:17:08Z
day: '30'
department:
- _id: NiBa
- _id: GaTk
doi: 10.25386/genetics.6148304.v1
main_file_link:
- open_access: '1'
  url: https://doi.org/10.25386/genetics.6148304.v1
month: '04'
oa: 1
oa_version: Published Version
publisher: Genetics Society of America
related_material:
  record:
  - id: '316'
    relation: used_in_publication
    status: public
status: public
title: Supplemental material for Bodova et al., 2018
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2018'
...
---
_id: '9837'
abstract:
- lang: eng
  text: Both classical and recent studies suggest that chromosomal inversion polymorphisms
    are important in adaptation and speciation. However, biases in discovery and reporting
    of inversions make it difficult to assess their prevalence and biological importance.
    Here, we use an approach based on linkage disequilibrium among markers genotyped
    for samples collected across a transect between contrasting habitats to detect
    chromosomal rearrangements de novo. We report 17 polymorphic rearrangements in
    a single locality for the coastal marine snail, Littorina saxatilis. Patterns
    of diversity in the field and of recombination in controlled crosses provide strong
    evidence that at least the majority of these rearrangements are inversions. Most
    show clinal changes in frequency between habitats, suggestive of divergent selection,
    but only one appears to be fixed for different arrangements in the two habitats.
    Consistent with widespread evidence for balancing selection on inversion polymorphisms,
    we argue that a combination of heterosis and divergent selection can explain the
    observed patterns and should be considered in other systems spanning environmental
    gradients.
article_processing_charge: No
author:
- first_name: Rui
  full_name: Faria, Rui
  last_name: Faria
- first_name: Pragya
  full_name: Chaube, Pragya
  last_name: Chaube
- first_name: Hernán E.
  full_name: Morales, Hernán E.
  last_name: Morales
- first_name: Tomas
  full_name: Larsson, Tomas
  last_name: Larsson
- first_name: Alan R.
  full_name: Lemmon, Alan R.
  last_name: Lemmon
- first_name: Emily M.
  full_name: Lemmon, Emily M.
  last_name: Lemmon
- first_name: Marina
  full_name: Rafajlović, Marina
  last_name: Rafajlović
- first_name: Marina
  full_name: Panova, Marina
  last_name: Panova
- first_name: Mark
  full_name: Ravinet, Mark
  last_name: Ravinet
- first_name: Kerstin
  full_name: Johannesson, Kerstin
  last_name: Johannesson
- first_name: Anja M
  full_name: Westram, Anja M
  id: 3C147470-F248-11E8-B48F-1D18A9856A87
  last_name: Westram
  orcid: 0000-0003-1050-4969
- first_name: Roger K.
  full_name: Butlin, Roger K.
  last_name: Butlin
citation:
  ama: 'Faria R, Chaube P, Morales HE, et al. Data from: Multiple chromosomal rearrangements
    in a hybrid zone between Littorina saxatilis ecotypes. 2018. doi:<a href="https://doi.org/10.5061/dryad.72cg113">10.5061/dryad.72cg113</a>'
  apa: 'Faria, R., Chaube, P., Morales, H. E., Larsson, T., Lemmon, A. R., Lemmon,
    E. M., … Butlin, R. K. (2018). Data from: Multiple chromosomal rearrangements
    in a hybrid zone between Littorina saxatilis ecotypes. Dryad. <a href="https://doi.org/10.5061/dryad.72cg113">https://doi.org/10.5061/dryad.72cg113</a>'
  chicago: 'Faria, Rui, Pragya Chaube, Hernán E. Morales, Tomas Larsson, Alan R. Lemmon,
    Emily M. Lemmon, Marina Rafajlović, et al. “Data from: Multiple Chromosomal Rearrangements
    in a Hybrid Zone between Littorina Saxatilis Ecotypes.” Dryad, 2018. <a href="https://doi.org/10.5061/dryad.72cg113">https://doi.org/10.5061/dryad.72cg113</a>.'
  ieee: 'R. Faria <i>et al.</i>, “Data from: Multiple chromosomal rearrangements in
    a hybrid zone between Littorina saxatilis ecotypes.” Dryad, 2018.'
  ista: 'Faria R, Chaube P, Morales HE, Larsson T, Lemmon AR, Lemmon EM, Rafajlović
    M, Panova M, Ravinet M, Johannesson K, Westram AM, Butlin RK. 2018. Data from:
    Multiple chromosomal rearrangements in a hybrid zone between Littorina saxatilis
    ecotypes, Dryad, <a href="https://doi.org/10.5061/dryad.72cg113">10.5061/dryad.72cg113</a>.'
  mla: 'Faria, Rui, et al. <i>Data from: Multiple Chromosomal Rearrangements in a
    Hybrid Zone between Littorina Saxatilis Ecotypes</i>. Dryad, 2018, doi:<a href="https://doi.org/10.5061/dryad.72cg113">10.5061/dryad.72cg113</a>.'
  short: R. Faria, P. Chaube, H.E. Morales, T. Larsson, A.R. Lemmon, E.M. Lemmon,
    M. Rafajlović, M. Panova, M. Ravinet, K. Johannesson, A.M. Westram, R.K. Butlin,
    (2018).
date_created: 2021-08-09T12:46:39Z
date_published: 2018-10-09T00:00:00Z
date_updated: 2023-08-24T14:50:26Z
day: '09'
department:
- _id: NiBa
doi: 10.5061/dryad.72cg113
main_file_link:
- open_access: '1'
  url: https://doi.org/10.5061/dryad.72cg113
month: '10'
oa: 1
oa_version: Published Version
publisher: Dryad
related_material:
  record:
  - id: '6095'
    relation: used_in_publication
    status: public
status: public
title: 'Data from: Multiple chromosomal rearrangements in a hybrid zone between Littorina
  saxatilis ecotypes'
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2018'
...
---
_id: '9840'
abstract:
- lang: eng
  text: Herd immunity, a process in which resistant individuals limit the spread of
    a pathogen among susceptible hosts has been extensively studied in eukaryotes.
    Even though bacteria have evolved multiple immune systems against their phage
    pathogens, herd immunity in bacteria remains unexplored. Here we experimentally
    demonstrate that herd immunity arises during phage epidemics in structured and
    unstructured Escherichia coli populations consisting of differing frequencies
    of susceptible and resistant cells harboring CRISPR immunity. In addition, we
    develop a mathematical model that quantifies how herd immunity is affected by
    spatial population structure, bacterial growth rate, and phage replication rate.
    Using our model we infer a general epidemiological rule describing the relative
    speed of an epidemic in partially resistant spatially structured populations.
    Our experimental and theoretical findings indicate that herd immunity may be important
    in bacterial communities, allowing for stable coexistence of bacteria and their
    phages and the maintenance of polymorphism in bacterial immunity.
article_processing_charge: No
author:
- first_name: Pavel
  full_name: Payne, Pavel
  id: 35F78294-F248-11E8-B48F-1D18A9856A87
  last_name: Payne
  orcid: 0000-0002-2711-9453
- first_name: Lukas
  full_name: Geyrhofer, Lukas
  last_name: Geyrhofer
- first_name: Nicholas H
  full_name: Barton, Nicholas H
  id: 4880FE40-F248-11E8-B48F-1D18A9856A87
  last_name: Barton
  orcid: 0000-0002-8548-5240
- first_name: Jonathan P
  full_name: Bollback, Jonathan P
  id: 2C6FA9CC-F248-11E8-B48F-1D18A9856A87
  last_name: Bollback
  orcid: 0000-0002-4624-4612
citation:
  ama: 'Payne P, Geyrhofer L, Barton NH, Bollback JP. Data from: CRISPR-based herd
    immunity limits phage epidemics in bacterial populations. 2018. doi:<a href="https://doi.org/10.5061/dryad.42n44">10.5061/dryad.42n44</a>'
  apa: 'Payne, P., Geyrhofer, L., Barton, N. H., &#38; Bollback, J. P. (2018). Data
    from: CRISPR-based herd immunity limits phage epidemics in bacterial populations.
    Dryad. <a href="https://doi.org/10.5061/dryad.42n44">https://doi.org/10.5061/dryad.42n44</a>'
  chicago: 'Payne, Pavel, Lukas Geyrhofer, Nicholas H Barton, and Jonathan P Bollback.
    “Data from: CRISPR-Based Herd Immunity Limits Phage Epidemics in Bacterial Populations.”
    Dryad, 2018. <a href="https://doi.org/10.5061/dryad.42n44">https://doi.org/10.5061/dryad.42n44</a>.'
  ieee: 'P. Payne, L. Geyrhofer, N. H. Barton, and J. P. Bollback, “Data from: CRISPR-based
    herd immunity limits phage epidemics in bacterial populations.” Dryad, 2018.'
  ista: 'Payne P, Geyrhofer L, Barton NH, Bollback JP. 2018. Data from: CRISPR-based
    herd immunity limits phage epidemics in bacterial populations, Dryad, <a href="https://doi.org/10.5061/dryad.42n44">10.5061/dryad.42n44</a>.'
  mla: 'Payne, Pavel, et al. <i>Data from: CRISPR-Based Herd Immunity Limits Phage
    Epidemics in Bacterial Populations</i>. Dryad, 2018, doi:<a href="https://doi.org/10.5061/dryad.42n44">10.5061/dryad.42n44</a>.'
  short: P. Payne, L. Geyrhofer, N.H. Barton, J.P. Bollback, (2018).
date_created: 2021-08-09T13:10:02Z
date_published: 2018-03-12T00:00:00Z
date_updated: 2025-04-15T08:17:50Z
day: '12'
department:
- _id: NiBa
- _id: JoBo
doi: 10.5061/dryad.42n44
main_file_link:
- open_access: '1'
  url: https://doi.org/10.5061/dryad.42n44
month: '03'
oa: 1
oa_version: Published Version
publisher: Dryad
related_material:
  record:
  - id: '423'
    relation: used_in_publication
    status: public
status: public
title: 'Data from: CRISPR-based herd immunity limits phage epidemics in bacterial
  populations'
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
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. <i>Algorithmica</i>.
    2018;80(5):1604-1633. doi:<a href="https://doi.org/10.1007/s00453-017-0369-2">10.1007/s00453-017-0369-2</a>
  apa: Oliveto, P., Paixao, T., Pérez Heredia, J., Sudholt, D., &#38; Trubenova, B.
    (2018). How to escape local optima in black box optimisation when non elitism
    outperforms elitism. <i>Algorithmica</i>. Springer. <a href="https://doi.org/10.1007/s00453-017-0369-2">https://doi.org/10.1007/s00453-017-0369-2</a>
  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.” <i>Algorithmica</i>. Springer, 2018. <a href="https://doi.org/10.1007/s00453-017-0369-2">https://doi.org/10.1007/s00453-017-0369-2</a>.
  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,” <i>Algorithmica</i>, 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.” <i>Algorithmica</i>, vol. 80, no. 5, Springer,
    2018, pp. 1604–33, doi:<a href="https://doi.org/10.1007/s00453-017-0369-2">10.1007/s00453-017-0369-2</a>.
  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: 2025-04-15T08:22:22Z
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: '1111'
abstract:
- lang: eng
  text: Adaptation depends critically on the effects of new mutations and their dependency
    on the genetic background in which they occur. These two factors can be summarized
    by the fitness landscape. However, it would require testing all mutations in all
    backgrounds, making the definition and analysis of fitness landscapes mostly inaccessible.
    Instead of postulating a particular fitness landscape, we address this problem
    by considering general classes of landscapes and calculating an upper limit for
    the time it takes for a population to reach a fitness peak, circumventing the
    need to have full knowledge about the fitness landscape. We analyze populations
    in the weak-mutation regime and characterize the conditions that enable them to
    quickly reach the fitness peak as a function of the number of sites under selection.
    We show that for additive landscapes there is a critical selection strength enabling
    populations to reach high-fitness genotypes, regardless of the distribution of
    effects. This threshold scales with the number of sites under selection, effectively
    setting a limit to adaptation, and results from the inevitable increase in deleterious
    mutational pressure as the population adapts in a space of discrete genotypes.
    Furthermore, we show that for the class of all unimodal landscapes this condition
    is sufficient but not necessary for rapid adaptation, as in some highly epistatic
    landscapes the critical strength does not depend on the number of sites under
    selection; effectively removing this barrier to adaptation.
article_processing_charge: No
article_type: original
author:
- first_name: Jorge
  full_name: Heredia, Jorge
  last_name: Heredia
- first_name: Barbora
  full_name: Trubenova, Barbora
  id: 42302D54-F248-11E8-B48F-1D18A9856A87
  last_name: Trubenova
  orcid: 0000-0002-6873-2967
- first_name: Dirk
  full_name: Sudholt, Dirk
  last_name: Sudholt
- first_name: Tiago
  full_name: Paixao, Tiago
  id: 2C5658E6-F248-11E8-B48F-1D18A9856A87
  last_name: Paixao
  orcid: 0000-0003-2361-3953
citation:
  ama: Heredia J, Trubenova B, Sudholt D, Paixao T. Selection limits to adaptive walks
    on correlated landscapes. <i>Genetics</i>. 2017;205(2):803-825. doi:<a href="https://doi.org/10.1534/genetics.116.189340">10.1534/genetics.116.189340</a>
  apa: Heredia, J., Trubenova, B., Sudholt, D., &#38; Paixao, T. (2017). Selection
    limits to adaptive walks on correlated landscapes. <i>Genetics</i>. Genetics Society
    of America. <a href="https://doi.org/10.1534/genetics.116.189340">https://doi.org/10.1534/genetics.116.189340</a>
  chicago: Heredia, Jorge, Barbora Trubenova, Dirk Sudholt, and Tiago Paixao. “Selection
    Limits to Adaptive Walks on Correlated Landscapes.” <i>Genetics</i>. Genetics
    Society of America, 2017. <a href="https://doi.org/10.1534/genetics.116.189340">https://doi.org/10.1534/genetics.116.189340</a>.
  ieee: J. Heredia, B. Trubenova, D. Sudholt, and T. Paixao, “Selection limits to
    adaptive walks on correlated landscapes,” <i>Genetics</i>, vol. 205, no. 2. Genetics
    Society of America, pp. 803–825, 2017.
  ista: Heredia J, Trubenova B, Sudholt D, Paixao T. 2017. Selection limits to adaptive
    walks on correlated landscapes. Genetics. 205(2), 803–825.
  mla: Heredia, Jorge, et al. “Selection Limits to Adaptive Walks on Correlated Landscapes.”
    <i>Genetics</i>, vol. 205, no. 2, Genetics Society of America, 2017, pp. 803–25,
    doi:<a href="https://doi.org/10.1534/genetics.116.189340">10.1534/genetics.116.189340</a>.
  short: J. Heredia, B. Trubenova, D. Sudholt, T. Paixao, Genetics 205 (2017) 803–825.
date_created: 2018-12-11T11:50:12Z
date_published: 2017-02-01T00:00:00Z
date_updated: 2026-06-18T10:46:55Z
day: '01'
ddc:
- '570'
department:
- _id: NiBa
doi: 10.1534/genetics.116.189340
ec_funded: 1
external_id:
  isi:
  - '000394144900025'
  pmid:
  - '27881471'
intvolume: '       205'
isi: 1
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.1534/genetics.116.189340
month: '02'
oa: 1
oa_version: Published Version
page: 803 - 825
pmid: 1
project:
- _id: 25B1EC9E-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '618091'
  name: Speed of Adaptation in Population Genetics and Evolutionary Computation
publication: Genetics
publication_identifier:
  issn:
  - 0016-6731
publication_status: published
publisher: Genetics Society of America
publist_id: '6256'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Selection limits to adaptive walks on correlated landscapes
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 205
year: '2017'
...
---
_id: '1112'
abstract:
- lang: eng
  text: There has been renewed interest in modelling the behaviour of evolutionary
    algorithms by more traditional mathematical objects, such as ordinary differential
    equations or Markov chains. The advantage is that the analysis becomes greatly
    facilitated due to the existence of well established methods. However, this typically
    comes at the cost of disregarding information about the process. Here, we introduce
    the use of stochastic differential equations (SDEs) for the study of EAs. SDEs
    can produce simple analytical results for the dynamics of stochastic processes,
    unlike Markov chains which can produce rigorous but unwieldy expressions about
    the dynamics. On the other hand, unlike ordinary differential equations (ODEs),
    they do not discard information about the stochasticity of the process. We show
    that these are especially suitable for the analysis of fixed budget scenarios
    and present analogs of the additive and multiplicative drift theorems for SDEs.
    We exemplify the use of these methods for two model algorithms ((1+1) EA and RLS)
    on two canonical problems(OneMax and LeadingOnes).
author:
- 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
citation:
  ama: 'Paixao T, Pérez Heredia J. An application of stochastic differential equations
    to evolutionary algorithms. In: <i>Proceedings of the 14th ACM/SIGEVO Conference
    on Foundations of Genetic Algorithms</i>. ACM; 2017:3-11. doi:<a href="https://doi.org/10.1145/3040718.3040729">10.1145/3040718.3040729</a>'
  apa: 'Paixao, T., &#38; Pérez Heredia, J. (2017). An application of stochastic differential
    equations to evolutionary algorithms. In <i>Proceedings of the 14th ACM/SIGEVO
    Conference on Foundations of Genetic Algorithms</i> (pp. 3–11). Copenhagen, Denmark:
    ACM. <a href="https://doi.org/10.1145/3040718.3040729">https://doi.org/10.1145/3040718.3040729</a>'
  chicago: Paixao, Tiago, and Jorge Pérez Heredia. “An Application of Stochastic Differential
    Equations to Evolutionary Algorithms.” In <i>Proceedings of the 14th ACM/SIGEVO
    Conference on Foundations of Genetic Algorithms</i>, 3–11. ACM, 2017. <a href="https://doi.org/10.1145/3040718.3040729">https://doi.org/10.1145/3040718.3040729</a>.
  ieee: T. Paixao and J. Pérez Heredia, “An application of stochastic differential
    equations to evolutionary algorithms,” in <i>Proceedings of the 14th ACM/SIGEVO
    Conference on Foundations of Genetic Algorithms</i>, Copenhagen, Denmark, 2017,
    pp. 3–11.
  ista: 'Paixao T, Pérez Heredia J. 2017. An application of stochastic differential
    equations to evolutionary algorithms. Proceedings of the 14th ACM/SIGEVO Conference
    on Foundations of Genetic Algorithms. FOGA: Foundations of Genetic Algorithms,
    3–11.'
  mla: Paixao, Tiago, and Jorge Pérez Heredia. “An Application of Stochastic Differential
    Equations to Evolutionary Algorithms.” <i>Proceedings of the 14th ACM/SIGEVO Conference
    on Foundations of Genetic Algorithms</i>, ACM, 2017, pp. 3–11, doi:<a href="https://doi.org/10.1145/3040718.3040729">10.1145/3040718.3040729</a>.
  short: T. Paixao, J. Pérez Heredia, in:, Proceedings of the 14th ACM/SIGEVO Conference
    on Foundations of Genetic Algorithms, ACM, 2017, pp. 3–11.
conference:
  end_date: 2017-01-15
  location: Copenhagen, Denmark
  name: 'FOGA: Foundations of Genetic Algorithms'
  start_date: 2017-01-12
date_created: 2018-12-11T11:50:12Z
date_published: 2017-01-12T00:00:00Z
date_updated: 2021-01-12T06:48:22Z
day: '12'
department:
- _id: NiBa
doi: 10.1145/3040718.3040729
language:
- iso: eng
month: '01'
oa_version: None
page: 3 - 11
publication: Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic
  Algorithms
publication_identifier:
  isbn:
  - 978-145034651-1
publication_status: published
publisher: ACM
publist_id: '6255'
quality_controlled: '1'
scopus_import: 1
status: public
title: An application of stochastic differential equations to evolutionary algorithms
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2017'
...
---
_id: '1169'
abstract:
- lang: eng
  text: Dispersal is a crucial factor in natural evolution, since it determines the
    habitat experienced by any population and defines the spatial scale of interactions
    between individuals. There is compelling evidence for systematic differences in
    dispersal characteristics within the same population, i.e., genotype-dependent
    dispersal. The consequences of genotype-dependent dispersal on other evolutionary
    phenomena, however, are poorly understood. In this article we investigate the
    effect of genotype-dependent dispersal on spatial gene frequency patterns, using
    a generalization of the classical diffusion model of selection and dispersal.
    Dispersal is characterized by the variance of dispersal (diffusion coefficient)
    and the mean displacement (directional advection term). We demonstrate that genotype-dependent
    dispersal may change the qualitative behavior of Fisher waves, which change from
    being “pulled” to being “pushed” wave fronts as the discrepancy in dispersal between
    genotypes increases. The speed of any wave is partitioned into components due
    to selection, genotype-dependent variance of dispersal, and genotype-dependent
    mean displacement. We apply our findings to wave fronts maintained by selection
    against heterozygotes. Furthermore, we identify a benefit of increased variance
    of dispersal, quantify its effect on the speed of the wave, and discuss the implications
    for the evolution of dispersal strategies.
article_processing_charge: No
author:
- first_name: Sebastian
  full_name: Novak, Sebastian
  id: 461468AE-F248-11E8-B48F-1D18A9856A87
  last_name: Novak
  orcid: 0000-0002-2519-824X
- first_name: Richard
  full_name: Kollár, Richard
  last_name: Kollár
citation:
  ama: Novak S, Kollár R. Spatial gene frequency waves under genotype dependent dispersal.
    <i>Genetics</i>. 2017;205(1):367-374. doi:<a href="https://doi.org/10.1534/genetics.116.193946">10.1534/genetics.116.193946</a>
  apa: Novak, S., &#38; Kollár, R. (2017). Spatial gene frequency waves under genotype
    dependent dispersal. <i>Genetics</i>. Genetics Society of America. <a href="https://doi.org/10.1534/genetics.116.193946">https://doi.org/10.1534/genetics.116.193946</a>
  chicago: Novak, Sebastian, and Richard Kollár. “Spatial Gene Frequency Waves under
    Genotype Dependent Dispersal.” <i>Genetics</i>. Genetics Society of America, 2017.
    <a href="https://doi.org/10.1534/genetics.116.193946">https://doi.org/10.1534/genetics.116.193946</a>.
  ieee: S. Novak and R. Kollár, “Spatial gene frequency waves under genotype dependent
    dispersal,” <i>Genetics</i>, vol. 205, no. 1. Genetics Society of America, pp.
    367–374, 2017.
  ista: Novak S, Kollár R. 2017. Spatial gene frequency waves under genotype dependent
    dispersal. Genetics. 205(1), 367–374.
  mla: Novak, Sebastian, and Richard Kollár. “Spatial Gene Frequency Waves under Genotype
    Dependent Dispersal.” <i>Genetics</i>, vol. 205, no. 1, Genetics Society of America,
    2017, pp. 367–74, doi:<a href="https://doi.org/10.1534/genetics.116.193946">10.1534/genetics.116.193946</a>.
  short: S. Novak, R. Kollár, Genetics 205 (2017) 367–374.
date_created: 2018-12-11T11:50:31Z
date_published: 2017-01-01T00:00:00Z
date_updated: 2025-07-10T11:50:13Z
day: '01'
ddc:
- '576'
department:
- _id: NiBa
doi: 10.1534/genetics.116.193946
ec_funded: 1
external_id:
  isi:
  - '000393677300025'
file:
- access_level: open_access
  checksum: 7c8ab79cda1f92760bbbbe0f53175bfc
  content_type: application/pdf
  creator: system
  date_created: 2018-12-12T10:10:43Z
  date_updated: 2020-07-14T12:44:37Z
  file_id: '4833'
  file_name: IST-2016-727-v1+1_SFC_Genetics_final.pdf
  file_size: 361500
  relation: main_file
file_date_updated: 2020-07-14T12:44:37Z
has_accepted_license: '1'
intvolume: '       205'
isi: 1
issue: '1'
language:
- iso: eng
month: '01'
oa: 1
oa_version: Submitted Version
page: 367 - 374
project:
- _id: 25B1EC9E-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '618091'
  name: Speed of Adaptation in Population Genetics and Evolutionary Computation
- _id: 25B07788-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '250152'
  name: Limits to selection in biology and in evolutionary computation
publication: Genetics
publication_identifier:
  issn:
  - 0016-6731
publication_status: published
publisher: Genetics Society of America
publist_id: '6188'
pubrep_id: '727'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Spatial gene frequency waves under genotype dependent dispersal
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 205
year: '2017'
...
---
_id: '1191'
abstract:
- lang: eng
  text: Variation in genotypes may be responsible for differences in dispersal rates,
    directional biases, and growth rates of individuals. These traits may favor certain
    genotypes and enhance their spatiotemporal spreading into areas occupied by the
    less advantageous genotypes. We study how these factors influence the speed of
    spreading in the case of two competing genotypes under the assumption that spatial
    variation of the total population is small compared to the spatial variation of
    the frequencies of the genotypes in the population. In that case, the dynamics
    of the frequency of one of the genotypes is approximately described by a generalized
    Fisher–Kolmogorov–Petrovskii–Piskunov (F–KPP) equation. This generalized F–KPP
    equation with (nonlinear) frequency-dependent diffusion and advection terms admits
    traveling wave solutions that characterize the invasion of the dominant genotype.
    Our existence results generalize the classical theory for traveling waves for
    the F–KPP with constant coefficients. Moreover, in the particular case of the
    quadratic (monostable) nonlinear growth–decay rate in the generalized F–KPP we
    study in detail the influence of the variance in diffusion and mean displacement
    rates of the two genotypes on the minimal wave propagation speed.
acknowledgement: "We thank Nick Barton, Katarína Bod’ová, and Sr\r\n-\r\ndan Sarikas
  for constructive feed-\r\nback and support. Furthermore, we would like to express
  our deep gratitude to the anonymous referees (one\r\nof whom, Jimmy Garnier, agreed
  to reveal his identity) and the editor Max Souza, for very helpful and\r\ndetailed
  comments and suggestions that significantly helped us to improve the manuscript.
  This project has\r\nreceived funding from the European Union’s Seventh Framework
  Programme for research, technological\r\ndevelopment and demonstration under Grant
  Agreement 618091 Speed of Adaptation in Population Genet-\r\nics and Evolutionary
  Computation (SAGE) and the European Research Council (ERC) Grant No. 250152\r\n(SN),
  from the Scientific Grant Agency of the Slovak Republic under the Grant 1/0459/13
  and by the Slovak\r\nResearch and Development Agency under the Contract No. APVV-14-0378
  (RK). RK would also like to\r\nthank IST Austria for its hospitality during the
  work on this project."
article_processing_charge: No
arxiv: 1
author:
- first_name: Richard
  full_name: Kollár, Richard
  last_name: Kollár
- first_name: Sebastian
  full_name: Novak, Sebastian
  id: 461468AE-F248-11E8-B48F-1D18A9856A87
  last_name: Novak
  orcid: 0000-0002-2519-824X
citation:
  ama: Kollár R, Novak S. Existence of traveling waves for the generalized F–KPP equation.
    <i>Bulletin of Mathematical Biology</i>. 2017;79(3):525-559. doi:<a href="https://doi.org/10.1007/s11538-016-0244-3">10.1007/s11538-016-0244-3</a>
  apa: Kollár, R., &#38; Novak, S. (2017). Existence of traveling waves for the generalized
    F–KPP equation. <i>Bulletin of Mathematical Biology</i>. Springer. <a href="https://doi.org/10.1007/s11538-016-0244-3">https://doi.org/10.1007/s11538-016-0244-3</a>
  chicago: Kollár, Richard, and Sebastian Novak. “Existence of Traveling Waves for
    the Generalized F–KPP Equation.” <i>Bulletin of Mathematical Biology</i>. Springer,
    2017. <a href="https://doi.org/10.1007/s11538-016-0244-3">https://doi.org/10.1007/s11538-016-0244-3</a>.
  ieee: R. Kollár and S. Novak, “Existence of traveling waves for the generalized
    F–KPP equation,” <i>Bulletin of Mathematical Biology</i>, vol. 79, no. 3. Springer,
    pp. 525–559, 2017.
  ista: Kollár R, Novak S. 2017. Existence of traveling waves for the generalized
    F–KPP equation. Bulletin of Mathematical Biology. 79(3), 525–559.
  mla: Kollár, Richard, and Sebastian Novak. “Existence of Traveling Waves for the
    Generalized F–KPP Equation.” <i>Bulletin of Mathematical Biology</i>, vol. 79,
    no. 3, Springer, 2017, pp. 525–59, doi:<a href="https://doi.org/10.1007/s11538-016-0244-3">10.1007/s11538-016-0244-3</a>.
  short: R. Kollár, S. Novak, Bulletin of Mathematical Biology 79 (2017) 525–559.
date_created: 2018-12-11T11:50:38Z
date_published: 2017-03-01T00:00:00Z
date_updated: 2025-09-22T09:44:54Z
day: '01'
department:
- _id: NiBa
doi: 10.1007/s11538-016-0244-3
ec_funded: 1
external_id:
  arxiv:
  - '1607.00944'
  isi:
  - '000395156200005'
intvolume: '        79'
isi: 1
issue: '3'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://arxiv.org/abs/1607.00944
month: '03'
oa: 1
oa_version: Preprint
page: 525-559
project:
- _id: 25B1EC9E-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '618091'
  name: Speed of Adaptation in Population Genetics and Evolutionary Computation
- _id: 25B07788-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '250152'
  name: Limits to selection in biology and in evolutionary computation
publication: Bulletin of Mathematical Biology
publication_status: published
publisher: Springer
publist_id: '6160'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Existence of traveling waves for the generalized F–KPP equation
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 79
year: '2017'
...
---
_id: '1199'
abstract:
- lang: eng
  text: Much of quantitative genetics is based on the ‘infinitesimal model’, under
    which selection has a negligible effect on the genetic variance. This is typically
    justified by assuming a very large number of loci with additive effects. However,
    it applies even when genes interact, provided that the number of loci is large
    enough that selection on each of them is weak relative to random drift. In the
    long term, directional selection will change allele frequencies, but even then,
    the effects of epistasis on the ultimate change in trait mean due to selection
    may be modest. Stabilising selection can maintain many traits close to their optima,
    even when the underlying alleles are weakly selected. However, the number of traits
    that can be optimised is apparently limited to ~4Ne by the ‘drift load’, and this
    is hard to reconcile with the apparent complexity of many organisms. Just as for
    the mutation load, this limit can be evaded by a particular form of negative epistasis.
    A more robust limit is set by the variance in reproductive success. This suggests
    that selection accumulates information most efficiently in the infinitesimal regime,
    when selection on individual alleles is weak, and comparable with random drift.
    A review of evidence on selection strength suggests that although most variance
    in fitness may be because of alleles with large Nes, substantial amounts of adaptation
    may be because of alleles in the infinitesimal regime, in which epistasis has
    modest effects.
article_processing_charge: No
author:
- first_name: Nicholas H
  full_name: Barton, Nicholas H
  id: 4880FE40-F248-11E8-B48F-1D18A9856A87
  last_name: Barton
  orcid: 0000-0002-8548-5240
citation:
  ama: Barton NH. How does epistasis influence the response to selection? <i>Heredity</i>.
    2017;118:96-109. doi:<a href="https://doi.org/10.1038/hdy.2016.109">10.1038/hdy.2016.109</a>
  apa: Barton, N. H. (2017). How does epistasis influence the response to selection?
    <i>Heredity</i>. Nature Publishing Group. <a href="https://doi.org/10.1038/hdy.2016.109">https://doi.org/10.1038/hdy.2016.109</a>
  chicago: Barton, Nicholas H. “How Does Epistasis Influence the Response to Selection?”
    <i>Heredity</i>. Nature Publishing Group, 2017. <a href="https://doi.org/10.1038/hdy.2016.109">https://doi.org/10.1038/hdy.2016.109</a>.
  ieee: N. H. Barton, “How does epistasis influence the response to selection?,” <i>Heredity</i>,
    vol. 118. Nature Publishing Group, pp. 96–109, 2017.
  ista: Barton NH. 2017. How does epistasis influence the response to selection? Heredity.
    118, 96–109.
  mla: Barton, Nicholas H. “How Does Epistasis Influence the Response to Selection?”
    <i>Heredity</i>, vol. 118, Nature Publishing Group, 2017, pp. 96–109, doi:<a href="https://doi.org/10.1038/hdy.2016.109">10.1038/hdy.2016.109</a>.
  short: N.H. Barton, Heredity 118 (2017) 96–109.
date_created: 2018-12-11T11:50:40Z
date_published: 2017-01-01T00:00:00Z
date_updated: 2025-04-15T07:11:02Z
day: '01'
department:
- _id: NiBa
doi: 10.1038/hdy.2016.109
ec_funded: 1
external_id:
  isi:
  - '000392229100011'
intvolume: '       118'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5176114/
month: '01'
oa: 1
oa_version: Submitted Version
page: 96 - 109
project:
- _id: 25B07788-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '250152'
  name: Limits to selection in biology and in evolutionary computation
publication: Heredity
publication_status: published
publisher: Nature Publishing Group
publist_id: '6151'
quality_controlled: '1'
related_material:
  record:
  - id: '9710'
    relation: research_data
    status: public
scopus_import: '1'
status: public
title: How does epistasis influence the response to selection?
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 118
year: '2017'
...
---
_id: '1336'
abstract:
- lang: eng
  text: Evolutionary algorithms (EAs) form a popular optimisation paradigm inspired
    by natural evolution. In recent years the field of evolutionary computation has
    developed a rigorous analytical theory to analyse the runtimes of EAs on many
    illustrative problems. Here we apply this theory to a simple model of natural
    evolution. In the Strong Selection Weak Mutation (SSWM) evolutionary regime the
    time between occurrences of new mutations is much longer than the time it takes
    for a mutated genotype to take over the population. In this situation, the population
    only contains copies of one genotype and evolution can be modelled as a stochastic
    process evolving one genotype by means of mutation and selection between the resident
    and the mutated genotype. The probability of accepting the mutated genotype then
    depends on the change in fitness. We study this process, SSWM, from an algorithmic
    perspective, quantifying its expected optimisation time for various parameters
    and investigating differences to a similar evolutionary algorithm, the well-known
    (1+1) EA. We show that SSWM can have a moderate advantage over the (1+1) EA at
    crossing fitness valleys and study an example where SSWM outperforms the (1+1)
    EA by taking advantage of information on the fitness gradient.
article_processing_charge: No
author:
- 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: Paixao T, Pérez Heredia J, Sudholt D, Trubenova B. Towards a runtime comparison
    of natural and artificial evolution. <i>Algorithmica</i>. 2017;78(2):681-713.
    doi:<a href="https://doi.org/10.1007/s00453-016-0212-1">10.1007/s00453-016-0212-1</a>
  apa: Paixao, T., Pérez Heredia, J., Sudholt, D., &#38; Trubenova, B. (2017). Towards
    a runtime comparison of natural and artificial evolution. <i>Algorithmica</i>.
    Springer. <a href="https://doi.org/10.1007/s00453-016-0212-1">https://doi.org/10.1007/s00453-016-0212-1</a>
  chicago: Paixao, Tiago, Jorge Pérez Heredia, Dirk Sudholt, and Barbora Trubenova.
    “Towards a Runtime Comparison of Natural and Artificial Evolution.” <i>Algorithmica</i>.
    Springer, 2017. <a href="https://doi.org/10.1007/s00453-016-0212-1">https://doi.org/10.1007/s00453-016-0212-1</a>.
  ieee: T. Paixao, J. Pérez Heredia, D. Sudholt, and B. Trubenova, “Towards a runtime
    comparison of natural and artificial evolution,” <i>Algorithmica</i>, vol. 78,
    no. 2. Springer, pp. 681–713, 2017.
  ista: Paixao T, Pérez Heredia J, Sudholt D, Trubenova B. 2017. Towards a runtime
    comparison of natural and artificial evolution. Algorithmica. 78(2), 681–713.
  mla: Paixao, Tiago, et al. “Towards a Runtime Comparison of Natural and Artificial
    Evolution.” <i>Algorithmica</i>, vol. 78, no. 2, Springer, 2017, pp. 681–713,
    doi:<a href="https://doi.org/10.1007/s00453-016-0212-1">10.1007/s00453-016-0212-1</a>.
  short: T. Paixao, J. Pérez Heredia, D. Sudholt, B. Trubenova, Algorithmica 78 (2017)
    681–713.
date_created: 2018-12-11T11:51:27Z
date_published: 2017-06-01T00:00:00Z
date_updated: 2026-04-16T09:55:33Z
day: '01'
ddc:
- '576'
department:
- _id: NiBa
- _id: CaGu
doi: 10.1007/s00453-016-0212-1
ec_funded: 1
external_id:
  isi:
  - '000400379500013'
file:
- access_level: open_access
  checksum: 7873f665a0c598ac747c908f34cb14b9
  content_type: application/pdf
  creator: system
  date_created: 2018-12-12T10:10:19Z
  date_updated: 2020-07-14T12:44:44Z
  file_id: '4805'
  file_name: IST-2016-658-v1+1_s00453-016-0212-1.pdf
  file_size: 710206
  relation: main_file
file_date_updated: 2020-07-14T12:44:44Z
has_accepted_license: '1'
intvolume: '        78'
isi: 1
issue: '2'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
page: 681 - 713
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_identifier:
  issn:
  - 0178-4617
publication_status: published
publisher: Springer
publist_id: '5931'
pubrep_id: '658'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Towards a runtime comparison of natural and artificial evolution
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: ba8df636-2132-11f1-aed0-ed93e2281fdd
volume: 78
year: '2017'
...
---
_id: '1351'
abstract:
- lang: eng
  text: The behaviour of gene regulatory networks (GRNs) is typically analysed using
    simulation-based statistical testing-like methods. In this paper, we demonstrate
    that we can replace this approach by a formal verification-like method that gives
    higher assurance and scalability. We focus on Wagner’s weighted GRN model with
    varying weights, which is used in evolutionary biology. In the model, weight parameters
    represent the gene interaction strength that may change due to genetic mutations.
    For a property of interest, we synthesise the constraints over the parameter space
    that represent the set of GRNs satisfying the property. We experimentally show
    that our parameter synthesis procedure computes the mutational robustness of GRNs—an
    important problem of interest in evolutionary biology—more efficiently than the
    classical simulation method. We specify the property in linear temporal logic.
    We employ symbolic bounded model checking and SMT solving to compute the space
    of GRNs that satisfy the property, which amounts to synthesizing a set of linear
    constraints on the weights.
article_processing_charge: No
author:
- first_name: Mirco
  full_name: Giacobbe, Mirco
  id: 3444EA5E-F248-11E8-B48F-1D18A9856A87
  last_name: Giacobbe
  orcid: 0000-0001-8180-0904
- first_name: Calin C
  full_name: Guet, Calin C
  id: 47F8433E-F248-11E8-B48F-1D18A9856A87
  last_name: Guet
  orcid: 0000-0001-6220-2052
- first_name: Ashutosh
  full_name: Gupta, Ashutosh
  id: 335E5684-F248-11E8-B48F-1D18A9856A87
  last_name: Gupta
- first_name: Thomas A
  full_name: Henzinger, Thomas A
  id: 40876CD8-F248-11E8-B48F-1D18A9856A87
  last_name: Henzinger
  orcid: 0000−0002−2985−7724
- first_name: Tiago
  full_name: Paixao, Tiago
  id: 2C5658E6-F248-11E8-B48F-1D18A9856A87
  last_name: Paixao
  orcid: 0000-0003-2361-3953
- first_name: Tatjana
  full_name: Petrov, Tatjana
  id: 3D5811FC-F248-11E8-B48F-1D18A9856A87
  last_name: Petrov
  orcid: 0000-0002-9041-0905
citation:
  ama: Giacobbe M, Guet CC, Gupta A, Henzinger TA, Paixao T, Petrov T. Model checking
    the evolution of gene regulatory networks. <i>Acta Informatica</i>. 2017;54(8):765-787.
    doi:<a href="https://doi.org/10.1007/s00236-016-0278-x">10.1007/s00236-016-0278-x</a>
  apa: Giacobbe, M., Guet, C. C., Gupta, A., Henzinger, T. A., Paixao, T., &#38; Petrov,
    T. (2017). Model checking the evolution of gene regulatory networks. <i>Acta Informatica</i>.
    Springer. <a href="https://doi.org/10.1007/s00236-016-0278-x">https://doi.org/10.1007/s00236-016-0278-x</a>
  chicago: Giacobbe, Mirco, Calin C Guet, Ashutosh Gupta, Thomas A Henzinger, Tiago
    Paixao, and Tatjana Petrov. “Model Checking the Evolution of Gene Regulatory Networks.”
    <i>Acta Informatica</i>. Springer, 2017. <a href="https://doi.org/10.1007/s00236-016-0278-x">https://doi.org/10.1007/s00236-016-0278-x</a>.
  ieee: M. Giacobbe, C. C. Guet, A. Gupta, T. A. Henzinger, T. Paixao, and T. Petrov,
    “Model checking the evolution of gene regulatory networks,” <i>Acta Informatica</i>,
    vol. 54, no. 8. Springer, pp. 765–787, 2017.
  ista: Giacobbe M, Guet CC, Gupta A, Henzinger TA, Paixao T, Petrov T. 2017. Model
    checking the evolution of gene regulatory networks. Acta Informatica. 54(8), 765–787.
  mla: Giacobbe, Mirco, et al. “Model Checking the Evolution of Gene Regulatory Networks.”
    <i>Acta Informatica</i>, vol. 54, no. 8, Springer, 2017, pp. 765–87, doi:<a href="https://doi.org/10.1007/s00236-016-0278-x">10.1007/s00236-016-0278-x</a>.
  short: M. Giacobbe, C.C. Guet, A. Gupta, T.A. Henzinger, T. Paixao, T. Petrov, Acta
    Informatica 54 (2017) 765–787.
corr_author: '1'
date_created: 2018-12-11T11:51:32Z
date_published: 2017-12-01T00:00:00Z
date_updated: 2025-07-10T11:50:42Z
day: '01'
ddc:
- '006'
- '576'
department:
- _id: ToHe
- _id: CaGu
- _id: NiBa
doi: 10.1007/s00236-016-0278-x
ec_funded: 1
external_id:
  isi:
  - '000414343200003'
file:
- access_level: open_access
  checksum: 4e661d9135d7f8c342e8e258dee76f3e
  content_type: application/pdf
  creator: dernst
  date_created: 2019-01-17T15:57:29Z
  date_updated: 2020-07-14T12:44:46Z
  file_id: '5841'
  file_name: 2017_ActaInformatica_Giacobbe.pdf
  file_size: 755241
  relation: main_file
file_date_updated: 2020-07-14T12:44:46Z
has_accepted_license: '1'
intvolume: '        54'
isi: 1
issue: '8'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
page: 765 - 787
project:
- _id: 25EE3708-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '267989'
  name: Quantitative Reactive Modeling
- _id: 25832EC2-B435-11E9-9278-68D0E5697425
  call_identifier: FWF
  grant_number: S 11407_N23
  name: Rigorous Systems Engineering
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
  call_identifier: FWF
  grant_number: Z211
  name: Formal methods for the design and analysis of complex systems
- _id: 25B1EC9E-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '618091'
  name: Speed of Adaptation in Population Genetics and Evolutionary Computation
- _id: 25681D80-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '291734'
  name: International IST Postdoc Fellowship Programme
- _id: 25B07788-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '250152'
  name: Limits to selection in biology and in evolutionary computation
publication: Acta Informatica
publication_identifier:
  issn:
  - 0001-5903
publication_status: published
publisher: Springer
publist_id: '5898'
pubrep_id: '649'
quality_controlled: '1'
related_material:
  record:
  - id: '1835'
    relation: earlier_version
    status: public
scopus_import: '1'
status: public
title: Model checking the evolution of gene regulatory networks
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: 54
year: '2017'
...
---
_id: '570'
abstract:
- lang: eng
  text: 'Most phenotypes are determined by molecular systems composed of specifically
    interacting molecules. However, unlike for individual components, little is known
    about the distributions of mutational effects of molecular systems as a whole.
    We ask how the distribution of mutational effects of a transcriptional regulatory
    system differs from the distributions of its components, by first independently,
    and then simultaneously, mutating a transcription factor and the associated promoter
    it represses. We find that the system distribution exhibits increased phenotypic
    variation compared to individual component distributions - an effect arising from
    intermolecular epistasis between the transcription factor and its DNA-binding
    site. In large part, this epistasis can be qualitatively attributed to the structure
    of the transcriptional regulatory system and could therefore be a common feature
    in prokaryotes. Counter-intuitively, intermolecular epistasis can alleviate the
    constraints of individual components, thereby increasing phenotypic variation
    that selection could act on and facilitating adaptive evolution. '
article_number: e28921
article_processing_charge: No
author:
- first_name: Mato
  full_name: Lagator, Mato
  id: 345D25EC-F248-11E8-B48F-1D18A9856A87
  last_name: Lagator
- first_name: Srdjan
  full_name: Sarikas, Srdjan
  id: 35F0286E-F248-11E8-B48F-1D18A9856A87
  last_name: Sarikas
- first_name: Hande
  full_name: Acar, Hande
  id: 2DDF136A-F248-11E8-B48F-1D18A9856A87
  last_name: Acar
  orcid: 0000-0003-1986-9753
- first_name: Jonathan P
  full_name: Bollback, Jonathan P
  id: 2C6FA9CC-F248-11E8-B48F-1D18A9856A87
  last_name: Bollback
  orcid: 0000-0002-4624-4612
- first_name: Calin C
  full_name: Guet, Calin C
  id: 47F8433E-F248-11E8-B48F-1D18A9856A87
  last_name: Guet
  orcid: 0000-0001-6220-2052
citation:
  ama: Lagator M, Sarikas S, Acar H, Bollback JP, Guet CC. Regulatory network structure
    determines patterns of intermolecular epistasis. <i>eLife</i>. 2017;6. doi:<a
    href="https://doi.org/10.7554/eLife.28921">10.7554/eLife.28921</a>
  apa: Lagator, M., Sarikas, S., Acar, H., Bollback, J. P., &#38; Guet, C. C. (2017).
    Regulatory network structure determines patterns of intermolecular epistasis.
    <i>ELife</i>. eLife Sciences Publications. <a href="https://doi.org/10.7554/eLife.28921">https://doi.org/10.7554/eLife.28921</a>
  chicago: Lagator, Mato, Srdjan Sarikas, Hande Acar, Jonathan P Bollback, and Calin
    C Guet. “Regulatory Network Structure Determines Patterns of Intermolecular Epistasis.”
    <i>ELife</i>. eLife Sciences Publications, 2017. <a href="https://doi.org/10.7554/eLife.28921">https://doi.org/10.7554/eLife.28921</a>.
  ieee: M. Lagator, S. Sarikas, H. Acar, J. P. Bollback, and C. C. Guet, “Regulatory
    network structure determines patterns of intermolecular epistasis,” <i>eLife</i>,
    vol. 6. eLife Sciences Publications, 2017.
  ista: Lagator M, Sarikas S, Acar H, Bollback JP, Guet CC. 2017. Regulatory network
    structure determines patterns of intermolecular epistasis. eLife. 6, e28921.
  mla: Lagator, Mato, et al. “Regulatory Network Structure Determines Patterns of
    Intermolecular Epistasis.” <i>ELife</i>, vol. 6, e28921, eLife Sciences Publications,
    2017, doi:<a href="https://doi.org/10.7554/eLife.28921">10.7554/eLife.28921</a>.
  short: M. Lagator, S. Sarikas, H. Acar, J.P. Bollback, C.C. Guet, ELife 6 (2017).
corr_author: '1'
date_created: 2018-12-11T11:47:14Z
date_published: 2017-11-13T00:00:00Z
date_updated: 2025-09-11T07:40:30Z
day: '13'
ddc:
- '576'
department:
- _id: CaGu
- _id: JoBo
- _id: NiBa
doi: 10.7554/eLife.28921
ec_funded: 1
external_id:
  isi:
  - '000425868200001'
file:
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  content_type: application/pdf
  creator: system
  date_created: 2018-12-12T10:14:42Z
  date_updated: 2020-07-14T12:47:10Z
  file_id: '5096'
  file_name: IST-2017-918-v1+1_elife-28921-figures-v3.pdf
  file_size: 8453470
  relation: main_file
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  content_type: application/pdf
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  date_created: 2018-12-12T10:14:43Z
  date_updated: 2020-07-14T12:47:10Z
  file_id: '5097'
  file_name: IST-2017-918-v1+2_elife-28921-v3.pdf
  file_size: 1953221
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file_date_updated: 2020-07-14T12:47:10Z
has_accepted_license: '1'
intvolume: '         6'
isi: 1
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '291734'
  name: International IST Postdoc Fellowship Programme
- _id: 2578D616-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '648440'
  name: Selective Barriers to Horizontal Gene Transfer
publication: eLife
publication_identifier:
  issn:
  - 2050-084X
publication_status: published
publisher: eLife Sciences Publications
publist_id: '7244'
pubrep_id: '918'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Regulatory network structure determines patterns of intermolecular epistasis
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 6
year: '2017'
...
