Genomic Analysis of the Hydrocarbon-Producing, Cellulolytic, Endophytic Fungus Ascocoryne sarcoides
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{"title"=>"Genomic analysis of the hydrocarbon-producing, cellulolytic, endophytic fungus ascocoryne sarcoides", "type"=>"journal", "authors"=>[{"first_name"=>"Tara A.", "last_name"=>"Gianoulis", "scopus_author_id"=>"15048053400"}, {"first_name"=>"Meghan A.", "last_name"=>"Griffin", "scopus_author_id"=>"7403310581"}, {"first_name"=>"Daniel J.", "last_name"=>"Spakowicz", "scopus_author_id"=>"23566974100"}, {"first_name"=>"Brian F.", "last_name"=>"Dunican", "scopus_author_id"=>"47560998700"}, {"first_name"=>"Cambria J.", "last_name"=>"Alpha", "scopus_author_id"=>"55161929500"}, {"first_name"=>"Andrea", "last_name"=>"Sboner", "scopus_author_id"=>"55884911800"}, {"first_name"=>"A.", "last_name"=>"Michael Sismour", "scopus_author_id"=>"55164724300"}, {"first_name"=>"Chinnappa", "last_name"=>"Kodira", "scopus_author_id"=>"6506334958"}, {"first_name"=>"Michael", "last_name"=>"Egholm", "scopus_author_id"=>"7003454634"}, {"first_name"=>"George M.", "last_name"=>"Church", "scopus_author_id"=>"7005451318"}, {"first_name"=>"Mark B.", "last_name"=>"Gerstein", "scopus_author_id"=>"24755400900"}, {"first_name"=>"Scott A.", "last_name"=>"Strobel", "scopus_author_id"=>"7102738187"}], "year"=>2012, "source"=>"PLoS Genetics", "identifiers"=>{"pmid"=>"22396667", "doi"=>"10.1371/journal.pgen.1002558", "sgr"=>"84859239291", "isbn"=>"1553-7404 (Electronic)\\n1553-7390 (Linking)", "scopus"=>"2-s2.0-84859239291", "issn"=>"15537390", "pui"=>"364556499"}, "id"=>"6f0469d5-810f-391a-ba5e-c27b701198cf", "abstract"=>"The microbial conversion of solid cellulosic biomass to liquid biofuels may provide a renewable energy source for transportation fuels. 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Scopus | Further Information

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Endophytes represent a promising group of organisms, as they are a mostly untapped reservoir of metabolic diversity. They are often able to degrade cellulose, and they can produce an extraordinary diversity of metabolites. The filamentous fungal endophyte <em>Ascocoryne sarcoides</em> was shown to produce potential-biofuel metabolites when grown on a cellulose-based medium; however, the genetic pathways needed for this production are unknown and the lack of genetic tools makes traditional reverse genetics difficult. We present the genomic characterization of <em>A. sarcoides</em> and use transcriptomic and metabolomic data to describe the genes involved in cellulose degradation and to provide hypotheses for the biofuel production pathways. In total, almost 80 biosynthetic clusters were identified, including several previously found only in plants. Additionally, many transcriptionally active regions outside of genes showed condition-specific expression, offering more evidence for the role of long non-coding RNA in gene regulation. This is one of the highest quality fungal genomes and, to our knowledge, the only thoroughly annotated and transcriptionally profiled fungal endophyte genome currently available. The analyses and datasets contribute to the study of cellulose degradation and biofuel production and provide the genomic foundation for the study of a model endophyte system.</p> </div>", "links"=>[], "tags"=>["genomic", "endophytic", "fungus"], "article_id"=>128170, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Tara A. Gianoulis", "Meghan A. Griffin", "Daniel J. Spakowicz", "Brian F. Dunican", "Cambria J. Alpha", "Andrea Sboner", "A. Michael Sismour", "Chinnappa Kodira", "Michael Egholm", "George M. Church", "Mark B. Gerstein", "Scott A. Strobel"], "doi"=>["https://dx.doi.org/10.1371/journal.pgen.1002558.s001", "https://dx.doi.org/10.1371/journal.pgen.1002558.s002", "https://dx.doi.org/10.1371/journal.pgen.1002558.s003", "https://dx.doi.org/10.1371/journal.pgen.1002558.s004", "https://dx.doi.org/10.1371/journal.pgen.1002558.s005", "https://dx.doi.org/10.1371/journal.pgen.1002558.s006", "https://dx.doi.org/10.1371/journal.pgen.1002558.s007", "https://dx.doi.org/10.1371/journal.pgen.1002558.s008", "https://dx.doi.org/10.1371/journal.pgen.1002558.s009", "https://dx.doi.org/10.1371/journal.pgen.1002558.s010", "https://dx.doi.org/10.1371/journal.pgen.1002558.s011", "https://dx.doi.org/10.1371/journal.pgen.1002558.s012", "https://dx.doi.org/10.1371/journal.pgen.1002558.s013", "https://dx.doi.org/10.1371/journal.pgen.1002558.s014", "https://dx.doi.org/10.1371/journal.pgen.1002558.s015", "https://dx.doi.org/10.1371/journal.pgen.1002558.s016", "https://dx.doi.org/10.1371/journal.pgen.1002558.s017", "https://dx.doi.org/10.1371/journal.pgen.1002558.s018", "https://dx.doi.org/10.1371/journal.pgen.1002558.s019", "https://dx.doi.org/10.1371/journal.pgen.1002558.s020", "https://dx.doi.org/10.1371/journal.pgen.1002558.s021", "https://dx.doi.org/10.1371/journal.pgen.1002558.s022", "https://dx.doi.org/10.1371/journal.pgen.1002558.s023", "https://dx.doi.org/10.1371/journal.pgen.1002558.s024", "https://dx.doi.org/10.1371/journal.pgen.1002558.s025", "https://dx.doi.org/10.1371/journal.pgen.1002558.s026", "https://dx.doi.org/10.1371/journal.pgen.1002558.s027", "https://dx.doi.org/10.1371/journal.pgen.1002558.s028", "https://dx.doi.org/10.1371/journal.pgen.1002558.s029", "https://dx.doi.org/10.1371/journal.pgen.1002558.s030", "https://dx.doi.org/10.1371/journal.pgen.1002558.s031"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Genomic_Analysis_of_the_Hydrocarbon_Producing_Cellulolytic_Endophytic_Fungus_Ascocoryne_sarcoides_/128170", "title"=>"Genomic Analysis of the Hydrocarbon-Producing, Cellulolytic, Endophytic Fungus <em>Ascocoryne sarcoides</em>", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-03-01 02:16:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/672971"], "description"=>"<p>(A) Schematic showing splice junction library generation. (B) For each of the three gene models shown, the x-axis is the genomic coordinates and the gray boxes represent individual exons, with arrows indicating strand. Reads having any overlap with the genic region are represented by black lines, the height of which correspond to the number of reads covering a particular base pair. Note that a read can align outside the exonic region, but that this was not observed at intron boundaries, although it did occur in the UTRs. (C) Schematic illustrating <i>de novo</i> assembly of reads into transcriptionally active regions (TARs). Three parameters are shown: threshold, min run, and max gap. Threshold sets the number of reads required for the region to be considered in the assembly. minRun sets the number of base pairs in the contiguous region required, and maxGap sets the number of discontiguous base pairs permitted to still be considered part of the assembly. Only the black box has sufficient base pairs above the threshold with the permitted contiguous length to be considered a TAR. (D) The minimum distance between each TAR and its nearest neighboring gene was computed. The number of TARs at least 1 kb away from any gene are shown (novel TARs). (E) Histogram of the length of novel TARs. Note the break in both the x and y-axis to indicate the outliers for TAR length and frequency. (F) Columns represent the culture growth conditions, rows individual novel TARs, and elements are color coded according to their RPKM value from white (no expression) to dark green (high expression).</p>", "links"=>[], "tags"=>["models"], "article_id"=>343454, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Tara A. Gianoulis", "Meghan A. Griffin", "Daniel J. Spakowicz", "Brian F. Dunican", "Cambria J. Alpha", "Andrea Sboner", "A. Michael Sismour", "Chinnappa Kodira", "Michael Egholm", "George M. Church", "Mark B. Gerstein", "Scott A. Strobel"], "doi"=>["https://dx.doi.org/10.1371/journal.pgen.1002558.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Validating_gene_models_and_novel_TARs_/343454", "title"=>"Validating gene models and novel TARs.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-03-01 00:57:34"}
  • {"files"=>["https://ndownloader.figshare.com/files/673072"], "description"=>"<p><i>A. sarcoides</i> transcription was profiled when grown on potato-dextrose media for 4 days (PD4), cellulose (CELL) and cellobiose (CB). (A) The total number of genes with quantile normalized log<sub>2</sub>(RPKM) greater than 2 was computed for each condition. The venn diagram shows the overlap of these genes across the three conditions. (B) Genes were partitioned according to their homology to the four main CAZY families: Glycoside Hydrolase (GH), Glucosyl Transferase (GT), Carbohydrate Esterase (CE), Carbohydrate Binding Modules (CBM). The homologs were then filtered to include only those genes which showed a standard deviation across the three conditions greater than 0.5. Each family was separately clustered (hierarchical, Euclidean distance, single linkage). The colorbar represents the quantile normalized log<sub>2</sub> (RPKM) value from white (low expression) to dark blue (high expression). Note: CBM can co-occur with all families. Only those genes that had exclusively a CBM domain were clustered in the CBM matrix to avoid duplication. (C) A table of the most highly expressed genes includes genes not directly involved in degradation, such as swollenin and chitin synthase (see <a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002558#s2\" target=\"_blank\">Results</a> for more details).</p>", "links"=>[], "tags"=>["cellulose-related"], "article_id"=>343550, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Tara A. Gianoulis", "Meghan A. Griffin", "Daniel J. Spakowicz", "Brian F. Dunican", "Cambria J. Alpha", "Andrea Sboner", "A. Michael Sismour", "Chinnappa Kodira", "Michael Egholm", "George M. Church", "Mark B. Gerstein", "Scott A. Strobel"], "doi"=>["https://dx.doi.org/10.1371/journal.pgen.1002558.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Analysis_of_cellulose_related_expression_/343550", "title"=>"Analysis of cellulose-related expression.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-03-01 00:59:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/673187"], "description"=>"<p>The top panels (A–D) represent the algorithm schema and the bottom panels (E–H) represent the corresponding steps with data for an example pathway, C8 production. Cyan, green, and purple are used to denote different experimental conditions (1, 2, and 3 and CB, PD4, and PD14 for the schematic and the C8 pathway data, respectively). GC/MS total ion chromatograms (orange box, A & E) are used to generate compound co-occurrence profiles (red box, B & F). These compound co-occurrence profiles are used to group and order the compounds based on patterns of correlation and anti-correlation to build a possible biosynthetic pathway (brown box C & G). Genes for which the expression profile matches the compound profile are considered correlated and therefore likely candidates for the biosynthetic pathway of interest (gray box D & H). Retrosynthesis is then used to match correlated genes with a reaction in the pathway, represented by roman numerals denoted on pathway arrows (brown box, C&G).</p>", "links"=>[], "tags"=>["transcriptomics", "metabolomics", "pathway"], "article_id"=>343665, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Tara A. Gianoulis", "Meghan A. Griffin", "Daniel J. Spakowicz", "Brian F. Dunican", "Cambria J. Alpha", "Andrea Sboner", "A. Michael Sismour", "Chinnappa Kodira", "Michael Egholm", "George M. Church", "Mark B. Gerstein", "Scott A. Strobel"], "doi"=>["https://dx.doi.org/10.1371/journal.pgen.1002558.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Coupled_transcriptomics_and_metabolomics_to_generate_pathway_predictions_/343665", "title"=>"Coupled transcriptomics and metabolomics to generate pathway predictions.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-03-01 01:01:05"}
  • {"files"=>["https://ndownloader.figshare.com/files/673286"], "description"=>"<p>Each plot shows the quantile-normalized log<sub>2</sub> (RPKM) for each set of genes of co-expressed with a particular compound profile (green 001, red 010, blue 100, cyan 101, purple 110, and black 111) across all 6 conditions (CB, PD4, PD14, AMM, CELL, and OAC). The first three conditions (CB, PD4, and PD14) represent the conditions where the compounds analyzed in this study were detected. The remaining conditions serve as the nulls (see <a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002558#pgen.1002558.s030\" target=\"_blank\">Text S1f</a>or details). Within the plots, each line corresponds to a single gene.</p>", "links"=>[], "tags"=>["co-expression"], "article_id"=>343767, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Tara A. Gianoulis", "Meghan A. Griffin", "Daniel J. Spakowicz", "Brian F. Dunican", "Cambria J. Alpha", "Andrea Sboner", "A. Michael Sismour", "Chinnappa Kodira", "Michael Egholm", "George M. Church", "Mark B. Gerstein", "Scott A. Strobel"], "doi"=>["https://dx.doi.org/10.1371/journal.pgen.1002558.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Compound_gene_co_expression_profiles_/343767", "title"=>"Compound gene co-expression profiles.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-03-01 01:02:47"}

PMC Usage Stats | Further Information

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  • {"unique-ip"=>"8", "full-text"=>"9", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"4"}
  • {"unique-ip"=>"10", "full-text"=>"9", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"6"}
  • {"unique-ip"=>"10", "full-text"=>"1", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"13", "cited-by"=>"0", "year"=>"2018", "month"=>"7"}
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  • {"unique-ip"=>"8", "full-text"=>"6", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
  • {"unique-ip"=>"13", "full-text"=>"21", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"7", "cited-by"=>"0", "year"=>"2018", "month"=>"9"}
  • {"unique-ip"=>"11", "full-text"=>"13", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"30", "cited-by"=>"0", "year"=>"2018", "month"=>"11"}
  • {"unique-ip"=>"12", "full-text"=>"11", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
  • {"unique-ip"=>"7", "full-text"=>"7", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"2"}
  • {"unique-ip"=>"9", "full-text"=>"8", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"2", "cited-by"=>"1", "year"=>"2019", "month"=>"3"}
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Relative Metric

{"start_date"=>"2012-01-01T00:00:00Z", "end_date"=>"2012-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences/Biotechnology", "average_usage"=>[320, 560, 691, 804, 916, 1011, 1117, 1228, 1328, 1420, 1506, 1584, 1651, 1749, 1836, 1909, 1982, 2053, 2131, 2188, 2276, 2372, 2441, 2540, 2627]}, {"subject_area"=>"/Engineering and technology", "average_usage"=>[308, 500, 607, 700, 782, 876, 957, 1039, 1128, 1214, 1290, 1365, 1431, 1496, 1560, 1634, 1695, 1772, 1839, 1908, 1972, 2043, 2106, 2179, 2246]}, {"subject_area"=>"/Engineering and technology/Energy and power", "average_usage"=>[365, 582, 731, 863, 973, 1115, 1239, 1365, 1485, 1568, 1645, 1725, 1826, 1898, 1976, 2029, 2100, 2198, 2265, 2365, 2434, 2496, 2557, 2672, 2801]}]}
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