CiteULike | Further Information

• {"link"=>{"url"=>"http://www.citeulike.org/user/roys/article/4935798"}, "post_time"=>"2014-04-07 22:01:22", "tag"=>["evolution", "phosphorylation", "post_translationsal", "ptm", "yeast"], "linkout"=>[{"type"=>"DOI", "url"=>"http://dx.doi.org/10.1371/journal.pbio.1000134"}, {"type"=>"Pubmed Central", "url"=>"http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2691599/"}, {"type"=>"Pubmed", "url"=>"http://view.ncbi.nlm.nih.gov/pubmed/19547744"}, {"type"=>"Hubmed", "url"=>"http://www.hubmed.org/display.cgi?uids=19547744"}], "username"=>"roys", "article_id"=>"4935798"}
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Mendeley | Further Information

{"title"=>"Evolution of phosphoregulation: Comparison of phosphorylation patterns across yeast species", "type"=>"journal", "authors"=>[{"first_name"=>"Pedro", "last_name"=>"Beltrao", "scopus_author_id"=>"23494578700"}, {"first_name"=>"Jonathan C.", "last_name"=>"Trinidad", "scopus_author_id"=>"6603006380"}, {"first_name"=>"Dorothea", "last_name"=>"Fiedler", "scopus_author_id"=>"7003744242"}, {"first_name"=>"Assen", "last_name"=>"Roguev", "scopus_author_id"=>"6602936938"}, {"first_name"=>"Wendell A.", "last_name"=>"Lim", "scopus_author_id"=>"7202378233"}, {"first_name"=>"Kevan M.", "last_name"=>"Shokat", "scopus_author_id"=>"35476692900"}, {"first_name"=>"Alma L.", "last_name"=>"Burlingame", "scopus_author_id"=>"35475505400"}, {"first_name"=>"Nevan J.", "last_name"=>"Krogan", "scopus_author_id"=>"6603946841"}], "year"=>2009, "source"=>"PLoS Biology", "identifiers"=>{"sgr"=>"67649972198", "doi"=>"10.1371/journal.pbio.1000134", "pui"=>"354863292", "pmid"=>"19547744", "scopus"=>"2-s2.0-67649972198", "issn"=>"15449173", "isbn"=>"1545-7885 (Electronic)\\r1544-9173 (Linking)"}, "id"=>"ffa0248b-5e47-3805-a8bd-dbb81dca0307", "abstract"=>"The extent by which different cellular components generate phenotypic diversity is an ongoing debate in evolutionary biology that is yet to be addressed by quantitative comparative studies. We conducted an in vivo mass-spectrometry study of the phosphoproteomes of three yeast species (Saccharomyces cerevisiae, Candida albicans, and Schizosaccharomyces pombe) in order to quantify the evolutionary rate of change of phosphorylation. We estimate that kinase-substrate interactions change, at most, two orders of magnitude more slowly than transcription factor (TF)-promoter interactions. Our computational analysis linking kinases to putative substrates recapitulates known phosphoregulation events and provides putative evolutionary histories for the kinase regulation of protein complexes across 11 yeast species. To validate these trends, we used the E-MAP approach to analyze over 2,000 quantitative genetic interactions in S. cerevisiae and Sc. pombe, which demonstrated that protein kinases, and to a greater extent TFs, show lower than average conservation of genetic interactions. We propose therefore that protein kinases are an important source of phenotypic diversity.", "link"=>"http://www.mendeley.com/research/evolution-phosphoregulation-comparison-phosphorylation-patterns-across-yeast-species", "reader_count"=>238, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>16, "Researcher"=>70, "Student > Doctoral Student"=>7, "Student > Ph. D. Student"=>77, "Student > Postgraduate"=>5, "Student > Master"=>17, "Other"=>7, "Student > Bachelor"=>13, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>1, "Professor"=>21}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>16, "Researcher"=>70, "Student > Doctoral Student"=>7, "Student > Ph. D. Student"=>77, "Student > Postgraduate"=>5, "Student > Master"=>17, "Other"=>7, "Student > Bachelor"=>13, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>1, "Professor"=>21}, "reader_count_by_subject_area"=>{"Unspecified"=>3, "Agricultural and Biological Sciences"=>175, "Chemical Engineering"=>1, "Chemistry"=>3, "Computer Science"=>6, "Engineering"=>5, "Environmental Science"=>1, "Biochemistry, Genetics and Molecular Biology"=>31, "Materials Science"=>1, "Mathematics"=>2, "Medicine and Dentistry"=>3, "Neuroscience"=>2, "Physics and Astronomy"=>3, "Psychology"=>1, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Materials Science"=>{"Materials Science"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>3}, "Physics and Astronomy"=>{"Physics and Astronomy"=>3}, "Psychology"=>{"Psychology"=>1}, "Mathematics"=>{"Mathematics"=>2}, "Unspecified"=>{"Unspecified"=>3}, "Environmental Science"=>{"Environmental Science"=>1}, "Chemical Engineering"=>{"Chemical Engineering"=>1}, "Engineering"=>{"Engineering"=>5}, "Chemistry"=>{"Chemistry"=>3}, "Neuroscience"=>{"Neuroscience"=>2}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>175}, "Computer Science"=>{"Computer Science"=>6}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>31}}, "reader_count_by_country"=>{"United States"=>18, "Japan"=>1, "United Kingdom"=>4, "Portugal"=>1, "Spain"=>2, "India"=>2, "Canada"=>3, "Netherlands"=>2, "Austria"=>1, "Belgium"=>1, "Denmark"=>1, "Brazil"=>2, "Mexico"=>1, "Slovenia"=>2, "Australia"=>1, "Germany"=>1}, "group_count"=>9}

ORCID | Further Information

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• {"type"=>"COMMENT", "annotationUri"=>"info:doi/10.1371/annotation/f001ed8b-3088-4deb-9935-f3ae23701853", "title"=>"On the evolution of protein length and phosphorylation sites", "body"=>"(Disclaimer: I am an author of this article)\n\nLars Juhl Jensen pointed out in a blog post that the average protein length of a group of proteins is a strong predictor of average number of phosphorylation sites. He suggested that this correlation could explain some of the observations from figure 1: http://larsjuhljensen.wordpress.com/2009/06/25/analysis-on-the-evolution-of-protein-length-and-phosphorylation-sites/\n\nTo address some of his concerns I have calculated, for each GO group, the average number of phosphorylation sites per amino-acid instead of phosphorylation sites per protein. There is only a small reduction in the correlations suggesting that the conservation of average protein size for the different GO groups explains only a small part of the observed correlations in figure 1a. For more details please see:\nhttp://pbeltrao.blogspot.com/2009/06/reply-on-evolution-of-protein-length.html ", "isRemoved"=>false, "created"=>"2009-06-26T06:11:22Z", "lastModified"=>"2009-06-26T06:11:22Z", "creator"=>{"userId"=>"57211"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>false}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pbio.1000134", "state"=>"published", "journals"=>{"PLoSBiology"=>{"journalKey"=>"PLoSBiology", "eIssn"=>"1545-7885", "title"=>"PLOS Biology"}}}, "replyTreeSize"=>0, "mostRecentActivity"=>"2009-06-26T06:11:22Z", "replies"=>[]}

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Figshare

• {"files"=>["https://ndownloader.figshare.com/files/893927"], "description"=>"<p>(A) Proteins of <i>S. cerevisiae</i>, <i>C. albicans</i>, and <i>Sc. pombe</i> were grouped according to gene ontology functions, and for each function we calculated the fraction of phosphosites per protein normalized by the average number of phosphosites per protein in the proteome. We plotted the relative levels of phosphorylation of <i>S. cerevisiae</i> functions against the same measure in <i>C. albicans</i>. The size of each point relates to the relative levels of phosphorylation in <i>Sc. pombe</i> that range from 1.2 to 2.4 arbitrary units. The individual correlation coefficients among the three species are <i>S. cerevisiae</i> versus <i>C. albicans</i> – <i>R</i>∼0.90; <i>S. cerevisiae</i> versus <i>Sc. pombe</i> – <i>R</i>∼0.91; <i>Sc. pombe</i> versus <i>C. albicans</i> – <i>R</i>∼0.88. Some functions were consistently found to be highly phosphorylated in all three species (annotated in the picture). (B and C) Proteins from the three species under study were grouped according to functional categories (B) or complex membership (C). For each group, the relative levels of phosphorylation were calculated for the three fungal species and represented in the form of a stacked graph. Those with a significant increase or decrease in phosphorylation are highlighted (see <a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000134#s4\" target=\"_blank\">Methods</a>). Asterisk indicates functions/complexes that also show a significant change in the relative fraction of phosphoproteins. Pound symbol (#) indicates functions/complexes that also show a significant difference in total number of proteins assigned in the orthologous group in the different species (see also <a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000134#pbio.1000134.s004\" target=\"_blank\">Protocol S1</a>).</p>", "links"=>[], "tags"=>["phosphorylation", "levels"], "article_id"=>564382, "categories"=>["Genetics", "Infectious Diseases", "Cell Biology", "Evolutionary Biology"], "users"=>["Pedro Beltrao", "Jonathan C. Trinidad", "Dorothea Fiedler", "Assen Roguev", "Wendell A. Lim", "Kevan M. Shokat", "Alma L. Burlingame", "Nevan J. Krogan"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.1000134.g001", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evolution_of_phosphorylation_levels_for_different_functional_groups_/564382", "title"=>"Evolution of phosphorylation levels for different functional groups.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-06-23 01:13:02"}
• {"files"=>["https://ndownloader.figshare.com/files/894322"], "description"=>"<p>Summary of phosphoproteins and phosphosites determined by MS analysis.</p>", "links"=>[], "tags"=>["phosphoproteins", "phosphosites", "ms"], "article_id"=>564774, "categories"=>["Genetics", "Infectious Diseases", "Cell Biology", "Evolutionary Biology"], "users"=>["Pedro Beltrao", "Jonathan C. Trinidad", "Dorothea Fiedler", "Assen Roguev", "Wendell A. Lim", "Kevan M. Shokat", "Alma L. Burlingame", "Nevan J. Krogan"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.1000134.t001", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summary_of_phosphoproteins_and_phosphosites_determined_by_MS_analysis_/564774", "title"=>"Summary of phosphoproteins and phosphosites determined by MS analysis.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2009-06-23 01:19:34"}
• {"files"=>["https://ndownloader.figshare.com/files/894187"], "description"=>"<p><i>S. cerevisiae</i>, <i>C. albicans</i>, and <i>Sc. pombe</i> proteins found to be phosphorylated experimentally are marked with a “P.” (A) For each protein phosphorylation propensity was predicted based on sequence (see <a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000134#s4\" target=\"_blank\">Methods</a>) and represented in a color intensity gradient where darker colors represent increasing predicted phosphorylation likelihood. The AROC value for the prediction of the phosphorylation pattern in the three species is 0.76 using the GPS method. White squares denote lack of predicted ortholog. (B) Casein kinase I type (Yck1p, Yck2p, Yck3p, and Hrr25p) phosphorylation propensity was predicted from sequence and classified as poor (white), weak (light blue), or strong (dark blue). Casein kinase type I phosphorylation propensity predicts this phosphorylation pattern with an AROC value of 0.63. Gray denotes lack of predicted ortholog.</p>", "links"=>[], "tags"=>["phosphoregulation", "clathrin"], "article_id"=>564643, "categories"=>["Genetics", "Infectious Diseases", "Cell Biology", "Evolutionary Biology"], "users"=>["Pedro Beltrao", "Jonathan C. Trinidad", "Dorothea Fiedler", "Assen Roguev", "Wendell A. Lim", "Kevan M. Shokat", "Alma L. Burlingame", "Nevan J. Krogan"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.1000134.g003", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evolution_of_phosphoregulation_of_the_Clathrin_associated_protein_complex_/564643", "title"=>"Evolution of phosphoregulation of the Clathrin associated protein complex.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-06-23 01:17:23"}
• {"files"=>["https://ndownloader.figshare.com/files/894270"], "description"=>"<p>Genetic interactions were compiled for orthologous gene pairs in <i>S. cerevisiae</i> and <i>Sc. pombe</i>. We compared the level of conservation of genetic interactions involving protein kinases and transcription factors to the average conservation of <i>S. cerevisiae</i> genetic interactions. The conservation of genetic interactions that overlap with protein–protein interactions were compared with physical interactions involving at least one protein kinase and with transient interactions. Physical interactions were defined as transient if they were experimentally determined by methods capable of capturing transient interactions (see <a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000134#s4\" target=\"_blank\">Methods</a>). The number of conserved interactions for each category is as follows: average gene pairs: 761 out of 5,322; kinases versus random genes: 38 out of 472; TFs versus random genes: 6 out of 141; physical interactions: 67 out of 233; transient interactions: 8 out of 85; kinase interactions: 2 out of 25; TF–gene interactions: 4 out of 48.</p>", "links"=>[], "tags"=>["divergence", "kinases", "transcription"], "article_id"=>564724, "categories"=>["Genetics", "Infectious Diseases", "Cell Biology", "Evolutionary Biology"], "users"=>["Pedro Beltrao", "Jonathan C. Trinidad", "Dorothea Fiedler", "Assen Roguev", "Wendell A. Lim", "Kevan M. Shokat", "Alma L. Burlingame", "Nevan J. Krogan"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.1000134.g004", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Functional_divergence_of_protein_kinases_and_transcription_factors_/564724", "title"=>"Functional divergence of protein kinases and transcription factors.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-06-23 01:18:44"}
• {"files"=>["https://ndownloader.figshare.com/files/442685", "https://ndownloader.figshare.com/files/442713", "https://ndownloader.figshare.com/files/442729", "https://ndownloader.figshare.com/files/442746"], "description"=>"<div><p>The extent by which different cellular components generate phenotypic diversity is an ongoing debate in evolutionary biology that is yet to be addressed by quantitative comparative studies. We conducted an in vivo mass-spectrometry study of the phosphoproteomes of three yeast species (<em>Saccharomyces cerevisiae</em>, <em>Candida albicans</em>, and <em>Schizosaccharomyces pombe</em>) in order to quantify the evolutionary rate of change of phosphorylation. We estimate that kinase–substrate interactions change, at most, two orders of magnitude more slowly than transcription factor (TF)–promoter interactions. Our computational analysis linking kinases to putative substrates recapitulates known phosphoregulation events and provides putative evolutionary histories for the kinase regulation of protein complexes across 11 yeast species. To validate these trends, we used the E-MAP approach to analyze over 2,000 quantitative genetic interactions in <em>S. cerevisiae</em> and <em>Sc. pombe</em>, which demonstrated that protein kinases, and to a greater extent TFs, show lower than average conservation of genetic interactions. We propose therefore that protein kinases are an important source of phenotypic diversity.</p></div>", "links"=>[], "tags"=>["phosphorylation", "patterns", "yeast"], "article_id"=>147246, "categories"=>["Genetics", "Cancer", "Cell Biology", "Evolutionary Biology"], "users"=>["Pedro Beltrao", "Jonathan C. Trinidad", "Dorothea Fiedler", "Assen Roguev", "Wendell A. Lim", "Kevan M. Shokat", "Alma L. Burlingame", "Nevan J. Krogan"], "doi"=>["https://dx.doi.org/10.1371/journal.pbio.1000134.s001", "https://dx.doi.org/10.1371/journal.pbio.1000134.s002", "https://dx.doi.org/10.1371/journal.pbio.1000134.s003", "https://dx.doi.org/10.1371/journal.pbio.1000134.s004"], "stats"=>{"downloads"=>20, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Evolution_of_Phosphoregulation_Comparison_of_Phosphorylation_Patterns_across_Yeast_Species/147246", "title"=>"Evolution of Phosphoregulation: Comparison of Phosphorylation Patterns across Yeast Species", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2009-06-23 02:00:46"}
• {"files"=>["https://ndownloader.figshare.com/files/894362"], "description"=>"<p>For each species studies, we calculated the rate of change of phosphoproteins and used this information to estimate the rate of change of kinase–substrate interactions. We considered only the set of identifiable <i>S. cerevisiae</i> orthologs and kinases that are orthologous to one of the 116 protein kinases of <i>S. cerevisiae</i>. In order to estimate the rate of change of kinase–substrate interactions, we assumed a gain or loss of a phosphoprotein would create or destroy one to five kinase–substrate interactions.</p>", "links"=>[], "tags"=>["phosphoproteins", "kinase-substrate"], "article_id"=>564810, "categories"=>["Genetics", "Infectious Diseases", "Cell Biology", "Evolutionary Biology"], "users"=>["Pedro Beltrao", "Jonathan C. Trinidad", "Dorothea Fiedler", "Assen Roguev", "Wendell A. Lim", "Kevan M. Shokat", "Alma L. Burlingame", "Nevan J. Krogan"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.1000134.t002", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Rate_of_change_of_phosphoproteins_and_kinase_substrate_interactions_/564810", "title"=>"Rate of change of phosphoproteins and kinase-substrate interactions.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2009-06-23 01:20:10"}
• {"files"=>["https://ndownloader.figshare.com/files/894018"], "description"=>"<p>For <i>S. cerevisiae</i>, <i>C. albicans</i>, and <i>Sc. pombe</i>, proteins found to be phosphorylated experimentally are marked with “P.” (A) For each protein in the species studied, phosphorylation propensity was predicted based on sequence (see <a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000134#s4\" target=\"_blank\">Methods</a>) and represented in a color intensity gradient, where darker colors represent increasing predicted phosphorylation likelihood. The AROC value for the prediction of the phosphorylation pattern the three species is 0.67 using the LR method. White squares denote lack of predicted ortholog. (B) The top five kinases predicted to be associated with the ORC and MCM complexes in <i>S. cerevisiae</i> are shown along with the respective AROC value and significance value for prediction of the phosphorylation pattern for the three species (C) Cdc28p phosphorylation propensity was predicted from sequence and classified as poor (white), weak (light blue), or strong (dark blue). Gray denotes lack of predicted ortholog.</p>", "links"=>[], "tags"=>["phosphoregulation", "pre-replication"], "article_id"=>564472, "categories"=>["Genetics", "Infectious Diseases", "Cell Biology", "Evolutionary Biology"], "users"=>["Pedro Beltrao", "Jonathan C. Trinidad", "Dorothea Fiedler", "Assen Roguev", "Wendell A. Lim", "Kevan M. Shokat", "Alma L. Burlingame", "Nevan J. Krogan"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.1000134.g002", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evolution_of_phosphoregulation_of_the_pre_replication_complex_/564472", "title"=>"Evolution of phosphoregulation of the pre-replication complex.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-06-23 01:14:32"}

PMC Usage Stats | Further Information

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Relative Metric

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F1000Prime