Under-Dominance Constrains the Evolution of Negative Autoregulation in Diploids
Publication Date
March 21, 2013
Journal
PLOS Computational Biology
Authors
Alexander J. Stewart, Robert M. Seymour, Andrew Pomiankowski & Max Reuter
Volume
9
Issue
3
Pages
e1002992
DOI
https://dx.plos.org/10.1371/journal.pcbi.1002992
Publisher URL
http://journals.plos.org/ploscompbiol/article?id=10.1371%2Fjournal.pcbi.1002992
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/23555226
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3605092
Europe PMC
http://europepmc.org/abstract/MED/23555226
Web of Science
000316864200061
Scopus
84875995560
Mendeley
http://www.mendeley.com/research/underdominance-constrains-evolution-negative-autoregulation-diploids
Events
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Mendeley | Further Information

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Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/993802"], "description"=>"<p>(a) Schematic representation of negative autoregulation when one (left) and two (right) copies of a gene are present in a cell. In the haploid the amount of negative autoregulation the gene experiences depends on on its own expression level. In the diploid, two gene copies are present (shown as light gray and dark gray), and the amount of negative autoregulation experienced by each gene depends on the expression level of <i>both</i> genes combined. If the two gene copies differ from one another in the strength of their transcription factor binding sites, complex dynamics can arise that are not observed in haploids. (b) IIllustration of variation in the repression function, , with protein concentration for different Hill coefficients, (sold line), (small dashes) and (large dashes).</p>", "links"=>[], "tags"=>["diploid"], "article_id"=>657118, "categories"=>["Evolutionary Biology"], "users"=>["Alexander J. Stewart", "Robert M. Seymour", "Andrew Pomiankowski", "Max Reuter"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002992.g001", "stats"=>{"downloads"=>2, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Cross_talk_in_diploid_autoregulators_/657118", "title"=>"Cross-talk in diploid autoregulators.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-22 04:52:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/993807"], "description"=>"<p>The figure shows quantitative results for the intrinsic noise of autoregulating genes, as measured by the ratio of the variance to mean expression in protein concentration at equilibrium. (a) Percentage change in the noise of a heterozygote compared to the resident homozygote. These are shown for different Hill coefficients, (black), (red) and (blue). Mutations become deleterious in the heterozygote when . (b) Percentage change in the noise of a mutant homozygote compared to the resident homozygote. Mutations become deleterious in the mutant homozygote when is about . The graphs show the results of stochastic simulations (see Materials and <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002992#s4\" target=\"_blank\">Methods</a>) for parameter values typical for transcription factors <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002992#pcbi.1002992-Thattai1\" target=\"_blank\">[3]</a>, , , , and . The resident homozygote has binding strength (as indicated by the x-axis), mutations are of size .</p>", "links"=>[], "tags"=>["Evolutionary biology"], "article_id"=>657123, "categories"=>["Evolutionary Biology"], "users"=>["Alexander J. Stewart", "Robert M. Seymour", "Andrew Pomiankowski", "Max Reuter"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002992.g005", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Intrinsic_noise_in_gene_expression_/657123", "title"=>"Intrinsic noise in gene expression.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-22 04:53:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/993806"], "description"=>"<p>Distribution of binding site strength achieved in evolutionary simulations for haploids (gray) and diploids (white). Hapoids are able to evolve stronger binding than diploids. The histograms shows results of replicate simulations for each ploidy level. The simulation procedure is described in the main text and the Materials and <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002992#s4\" target=\"_blank\">Methods</a>. The optimal binding strength used was , corresponding to a a background transcription rate .</p>", "links"=>[], "tags"=>["autoregulatory", "binding"], "article_id"=>657122, "categories"=>["Evolutionary Biology"], "users"=>["Alexander J. Stewart", "Robert M. Seymour", "Andrew Pomiankowski", "Max Reuter"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002992.g004", "stats"=>{"downloads"=>0, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evolution_of_autoregulatory_binding_sites_/657122", "title"=>"Evolution of autoregulatory binding sites.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-22 04:53:13"}
  • {"files"=>["https://ndownloader.figshare.com/files/993808", "https://ndownloader.figshare.com/files/993809", "https://ndownloader.figshare.com/files/993810", "https://ndownloader.figshare.com/files/993812", "https://ndownloader.figshare.com/files/993813", "https://ndownloader.figshare.com/files/993815", "https://ndownloader.figshare.com/files/993816", "https://ndownloader.figshare.com/files/993818", "https://ndownloader.figshare.com/files/993820"], "description"=>"<div><p>Regulatory networks have evolved to allow gene expression to rapidly track changes in the environment as well as to buffer perturbations and maintain cellular homeostasis in the absence of change. Theoretical work and empirical investigation in <i>Escherichia coli</i> have shown that negative autoregulation confers both rapid response times and reduced intrinsic noise, which is reflected in the fact that almost half of <i>Escherichia coli</i> transcription factors are negatively autoregulated. However, negative autoregulation is rare amongst the transcription factors of <i>Saccharomyces cerevisiae</i>. This difference is surprising because <i>E. coli</i> and <i>S. cerevisiae</i> otherwise have similar profiles of network motifs. In this study we investigate regulatory interactions amongst the transcription factors of <i>Drosophila melanogaster</i> and humans, and show that they have a similar dearth of negative autoregulation to that seen in <i>S. cerevisiae</i>. We then present a model demonstrating that this stiking difference in the noise reduction strategies used amongst species can be explained by constraints on the evolution of negative autoregulation in diploids. We show that regulatory interactions between pairs of homologous genes within the same cell can lead to under-dominance — mutations which result in stronger autoregulation, and decrease noise in homozygotes, paradoxically can cause increased noise in heterozygotes. This severely limits a diploid's ability to evolve negative autoregulation as a noise reduction mechanism. Our work offers a simple and general explanation for a previously unexplained difference between the regulatory architectures of <i>E. coli</i> and yeast, <i>Drosophila</i> and humans. It also demonstrates that the effects of diploidy in gene networks can have counter-intuitive consequences that may profoundly influence the course of evolution.</p> </div>", "links"=>[], "tags"=>["under-dominance", "constrains", "autoregulation", "diploids"], "article_id"=>657124, "categories"=>["Evolutionary Biology"], "users"=>["Alexander J. Stewart", "Robert M. Seymour", "Andrew Pomiankowski", "Max Reuter"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1002992.s001", "https://dx.doi.org/10.1371/journal.pcbi.1002992.s002", "https://dx.doi.org/10.1371/journal.pcbi.1002992.s003", "https://dx.doi.org/10.1371/journal.pcbi.1002992.s004", "https://dx.doi.org/10.1371/journal.pcbi.1002992.s005", "https://dx.doi.org/10.1371/journal.pcbi.1002992.s006", "https://dx.doi.org/10.1371/journal.pcbi.1002992.s007", "https://dx.doi.org/10.1371/journal.pcbi.1002992.s008", "https://dx.doi.org/10.1371/journal.pcbi.1002992.s009"], "stats"=>{"downloads"=>17, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Under_Dominance_Constrains_the_Evolution_of_Negative_Autoregulation_in_Diploids__/657124", "title"=>"Under-Dominance Constrains the Evolution of Negative Autoregulation in Diploids", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-03-22 04:53:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/993805"], "description"=>"<p>This figure shows quantitative results for the contributions of different alleles to expression and to response time. (a) Expression level of the resident allele (black line) and the mutant allele (red line) in the heterozygote relative to the resident allele in the homozygote. As binding strength increases the resident allele is over-expressed. (b) Response times for individual alleles (time to return to of the equilibrium expression level) in the heterozygote. The response time of the resident allele (black line) and the mutant allele (red line) in the heterozygote are shown relative to the response time of the resident allele in the homozygote. The resident allele in the heterozygote shows an increased response time with increasing binding strength. Mutant alleles in these graphs have dissociation constant , and the optimal binding strength in these graphs is , corresponding to a background transcription rate .</p>", "links"=>[], "tags"=>["times", "allele"], "article_id"=>657121, "categories"=>["Evolutionary Biology"], "users"=>["Alexander J. Stewart", "Robert M. Seymour", "Andrew Pomiankowski", "Max Reuter"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002992.g003", "stats"=>{"downloads"=>3, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Response_times_and_allele_expression_/657121", "title"=>"Response times and allele expression.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-22 04:53:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/993803"], "description"=>"<p>The response time of mutant (a) homozygotes and (b) heterozygotes are shown. Different values of the binding strength of the resident allele, in units of (x-axis), are plotted against mutations to binding site strength of different size (y-axis). Thus the graphs compare a resident allele, with a mutant allele, . Mutations falling into white region result in decreased response time in the carrier compared to resident genotype and are favoured by selection; mutations falling into the gray region result in increased response time and are not favoured by selection. Weak binding occurs when <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002992#pcbi.1002992-Becskei1\" target=\"_blank\">[1]</a>, <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002992#pcbi.1002992-Rosenfeld1\" target=\"_blank\">[2]</a>. Response times were calculated by numerically integrating <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002992#pcbi.1002992.e013\" target=\"_blank\">Eq. 1</a> from zero protein concentration to 90% of the equilibrium. The optimal binding strength in these graphs is , corresponding to a background transcription rate .</p>", "links"=>[], "tags"=>["autoregulatory", "binding"], "article_id"=>657119, "categories"=>["Evolutionary Biology"], "users"=>["Alexander J. Stewart", "Robert M. Seymour", "Andrew Pomiankowski", "Max Reuter"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002992.g002", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Invasibility_of_autoregulatory_binding_sites_/657119", "title"=>"Invasibility of autoregulatory binding sites.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-22 04:52:48"}

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  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"2"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2019", "month"=>"4"}

Relative Metric

{"start_date"=>"2013-01-01T00:00:00Z", "end_date"=>"2013-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences", "average_usage"=>[269, 466, 588, 697, 800, 896, 988, 1076, 1165, 1254, 1340, 1417]}, {"subject_area"=>"/Biology and life sciences/Biochemistry", "average_usage"=>[266, 468, 593, 703, 804, 903, 993, 1084, 1171, 1256, 1339, 1422, 1492]}, {"subject_area"=>"/Engineering and technology/Signal processing", "average_usage"=>[248, 406, 514, 603, 689, 787, 859, 930, 1027, 1083, 1131, 1201, 1270]}]}
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