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<!DOCTYPE html> <html lang="en" dir="ltr" xmlns="http://www.w3.org/1999/xhtml" xmlns:mml="http://www.w3.org/1998/Math/MathML"> <head prefix="og: http://ogp.me/ns# article: http://ogp.me/ns/article# book: http://ogp.me/ns/book#"><script type="text/javascript" src="https://web-static.archive.org/_static/js/bundle-playback.js?v=7YQSqjSh" charset="utf-8"></script> <script type="text/javascript" src="https://web-static.archive.org/_static/js/wombat.js?v=txqj7nKC" charset="utf-8"></script> <script>window.RufflePlayer=window.RufflePlayer||{};window.RufflePlayer.config={"autoplay":"on","unmuteOverlay":"hidden"};</script> <script type="text/javascript" src="https://web-static.archive.org/_static/js/ruffle/ruffle.js"></script> <script type="text/javascript"> __wm.init("https://web.archive.org/web"); __wm.wombat("https://www.biorxiv.org/content/10.1101/254250v1","20250130121542","https://web.archive.org/","web","https://web-static.archive.org/_static/", "1738239342"); </script> <link rel="stylesheet" type="text/css" href="https://web-static.archive.org/_static/css/banner-styles.css?v=p7PEIJWi" /> <link rel="stylesheet" type="text/css" href="https://web-static.archive.org/_static/css/iconochive.css?v=3PDvdIFv" />   <link rel="dns-prefetch" href="//web.archive.org/web/20250130121542/https://d33xdlntwy0kbs.cloudfront.net/"/> <link rel="dns-prefetch" href="//web.archive.org/web/20250130121542/https://www.google.com/"/> <link rel="dns-prefetch" href="//web.archive.org/web/20250130121542/https://scholar.google.com/"/> <link rel="dns-prefetch" href="//web.archive.org/web/20250130121542/https://www.googletagmanager.com/"/> <meta http-equiv="Content-Type" content="text/html; charset=utf-8"/> <link rel="shortcut icon" href="https://web.archive.org/web/20250130121542im_/https://www.biorxiv.org/sites/default/files/images/favicon.ico" type="image/vnd.microsoft.icon"/> <meta name="viewport" content="width=device-width, initial-scale=1"/> <link rel="alternate" type="application/pdf" title="Full Text (PDF)" href="/web/20250130121542/https://www.biorxiv.org/content/10.1101/254250v1.full.pdf"/> <link rel="alternate" type="text/plain" title="Full Text (Plain)" href="/web/20250130121542/https://www.biorxiv.org/content/10.1101/254250v1.full.txt"/> <meta name="type" content="article"/> <meta name="category" content="article"/> <meta name="HW.identifier" content="/biorxiv/early/2018/02/02/254250.atom"/> <meta name="HW.pisa" content="biorxiv;254250v1"/> <meta name="DC.Format" content="text/html"/> <meta name="DC.Language" content="en"/> <meta name="DC.Title" content="Proteomics as a metrological tool to evaluate genome annotation accuracy following de novo genome assembly: a case study using the Atlantic bottlenose dolphin (Tursiops truncatus)"/> <meta name="DC.Identifier" content="10.1101/254250"/> <meta name="DC.Date" content="2018-02-02"/> <meta name="DC.Publisher" content="Cold Spring Harbor Laboratory"/> <meta name="DC.Rights" content="漏 2018, Posted by Cold Spring Harbor Laboratory. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license"/> <meta name="DC.AccessRights" content="restricted"/> <meta name="DC.Description" content="Background The last decade has witnessed dramatic improvements in whole-genome sequencing capabilities coupled to drastically decreased costs, leading to an inundation of high-quality de novo genomes. For this reason, continued development of genome quality metrics is imperative. The current study utilized the recently updated Atlantic bottlenose dolphin ( Tursiops truncatus) genome and annotation to evaluate a proteomics-based metric of genome accuracy. Results Proteomic analysis of six tissues provided experimental confirmation of 10 402 proteins from 4 711 protein groups, almost 1/3 of the possible predicted proteins in the genome. There was an increased median molecular weight and number of identified peptides per protein using the current T. truncatus annotation versus the previous annotation. Identification of larger proteins with more identified peptides implied reduced database fragmentation and improved gene annotation accuracy. A metric is proposed, NP10, that attempts to capture this quality improvement. When using the new T. truncatus genome there was a 21 % improvement in NP10. This metric was further demonstrated by using a publicly available proteomic data set to compare human genome annotations from 2004, 2013 and 2016, which had a 33 % improvement in NP10. Conclusions These results demonstrate that new whole-genome sequencing techniques can rapidly generate high quality de novo genome assemblies and emphasizes the speed of advancing bioanalytical measurements in a non-model organism. Moreover, proteomics may be a useful metrological tool to benchmark genome accuracy, though there is a need for reference proteomic datasets to facilitate this utility in new de novo and existing genomes."/> <meta name="DC.Contributor" content="Benjamin A. Neely"/> <meta name="DC.Contributor" content="Debra L. Ellisor"/> <meta name="DC.Contributor" content="W. Clay Davis"/> <meta name="article:published_time" content="2018-02-02"/> <meta name="article:section" content="New Results"/> <meta name="citation_title" content="Proteomics as a metrological tool to evaluate genome annotation accuracy following de novo genome assembly: a case study using the Atlantic bottlenose dolphin (Tursiops truncatus)"/> <meta name="citation_abstract" lang="en" content="<h3>Abstract</h3> <h3>Background</h3> <p>The last decade has witnessed dramatic improvements in whole-genome sequencing capabilities coupled to drastically decreased costs, leading to an inundation of high-quality <i>de novo</i> genomes. For this reason, continued development of genome quality metrics is imperative. The current study utilized the recently updated Atlantic bottlenose dolphin (<i>Tursiops truncatus)</i> genome and annotation to evaluate a proteomics-based metric of genome accuracy.</p><h3>Results</h3> <p>Proteomic analysis of six tissues provided experimental confirmation of 10 402 proteins from 4 711 protein groups, almost 1/3 of the possible predicted proteins in the genome. There was an increased median molecular weight and number of identified peptides per protein using the current <i>T. truncatus</i> annotation versus the previous annotation. Identification of larger proteins with more identified peptides implied reduced database fragmentation and improved gene annotation accuracy. A metric is proposed, NP10, that attempts to capture this quality improvement. When using the new <i>T. truncatus</i> genome there was a 21 % improvement in NP10. This metric was further demonstrated by using a publicly available proteomic data set to compare human genome annotations from 2004, 2013 and 2016, which had a 33 % improvement in NP10.</p><h3>Conclusions</h3> <p>These results demonstrate that new whole-genome sequencing techniques can rapidly generate high quality <i>de novo</i> genome assemblies and emphasizes the speed of advancing bioanalytical measurements in a non-model organism. Moreover, proteomics may be a useful metrological tool to benchmark genome accuracy, though there is a need for reference proteomic datasets to facilitate this utility in new <i>de novo</i> and existing genomes.</p>"/> <meta name="citation_journal_title" content="bioRxiv"/> <meta name="citation_publisher" content="Cold Spring Harbor Laboratory"/> <meta name="citation_publication_date" content="2018/01/01"/> <meta name="citation_mjid" content="biorxiv;254250v1"/> <meta name="citation_id" content="254250v1"/> <meta name="citation_public_url" content="https://www.biorxiv.org/content/10.1101/254250v1"/> <meta name="citation_abstract_html_url" content="https://www.biorxiv.org/content/10.1101/254250v1.abstract"/> <meta name="citation_full_html_url" content="https://www.biorxiv.org/content/10.1101/254250v1.full"/> <meta name="citation_pdf_url" content="https://www.biorxiv.org/content/biorxiv/early/2018/02/02/254250.full.pdf"/> <meta name="citation_doi" content="10.1101/254250"/> <meta name="citation_num_pages" content="28"/> <meta name="citation_article_type" content="Article"/> <meta name="citation_section" content="New Results"/> <meta name="citation_firstpage" content="254250"/> <meta name="citation_author" content="Benjamin A. 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Nucleic Acids Res. 2016;44 D1:D67-72. doi:10.1093/nar/gkv1276."/> <meta name="twitter:title" content="Proteomics as a metrological tool to evaluate genome annotation accuracy following de novo genome assembly: a case study using the Atlantic bottlenose dolphin (Tursiops truncatus)"/> <meta name="twitter:site" content="@biorxivpreprint"/> <meta name="twitter:card" content="summary"/> <meta name="twitter:image" content="https://web.archive.org/web/20250130121542im_/https://www.biorxiv.org/sites/default/files/images/biorxiv_logo_homepage7-5-small.png"/> <meta name="twitter:description" content="Background The last decade has witnessed dramatic improvements in whole-genome sequencing capabilities coupled to drastically decreased costs, leading to an inundation of high-quality de novo genomes. For this reason, continued development of genome quality metrics is imperative. The current study utilized the recently updated Atlantic bottlenose dolphin ( Tursiops truncatus) genome and annotation to evaluate a proteomics-based metric of genome accuracy. Results Proteomic analysis of six tissues provided experimental confirmation of 10 402 proteins from 4 711 protein groups, almost 1/3 of the possible predicted proteins in the genome. There was an increased median molecular weight and number of identified peptides per protein using the current T. truncatus annotation versus the previous annotation. Identification of larger proteins with more identified peptides implied reduced database fragmentation and improved gene annotation accuracy. A metric is proposed, NP10, that attempts to capture this quality improvement. When using the new T. truncatus genome there was a 21 % improvement in NP10. This metric was further demonstrated by using a publicly available proteomic data set to compare human genome annotations from 2004, 2013 and 2016, which had a 33 % improvement in NP10. Conclusions These results demonstrate that new whole-genome sequencing techniques can rapidly generate high quality de novo genome assemblies and emphasizes the speed of advancing bioanalytical measurements in a non-model organism. Moreover, proteomics may be a useful metrological tool to benchmark genome accuracy, though there is a need for reference proteomic datasets to facilitate this utility in new de novo and existing genomes."/> <meta name="og-title" property="og:title" content="Proteomics as a metrological tool to evaluate genome annotation accuracy following de novo genome assembly: a case study using the Atlantic bottlenose dolphin (Tursiops truncatus)"/> <meta name="og-url" property="og:url" content="https://web.archive.org/web/20250130121542/https://www.biorxiv.org/content/10.1101/254250v1"/> <meta name="og-site-name" property="og:site_name" content="bioRxiv"/> <meta name="og-description" property="og:description" content="Background The last decade has witnessed dramatic improvements in whole-genome sequencing capabilities coupled to drastically decreased costs, leading to an inundation of high-quality de novo genomes. For this reason, continued development of genome quality metrics is imperative. The current study utilized the recently updated Atlantic bottlenose dolphin ( Tursiops truncatus) genome and annotation to evaluate a proteomics-based metric of genome accuracy. Results Proteomic analysis of six tissues provided experimental confirmation of 10 402 proteins from 4 711 protein groups, almost 1/3 of the possible predicted proteins in the genome. There was an increased median molecular weight and number of identified peptides per protein using the current T. truncatus annotation versus the previous annotation. Identification of larger proteins with more identified peptides implied reduced database fragmentation and improved gene annotation accuracy. A metric is proposed, NP10, that attempts to capture this quality improvement. When using the new T. truncatus genome there was a 21 % improvement in NP10. This metric was further demonstrated by using a publicly available proteomic data set to compare human genome annotations from 2004, 2013 and 2016, which had a 33 % improvement in NP10. Conclusions These results demonstrate that new whole-genome sequencing techniques can rapidly generate high quality de novo genome assemblies and emphasizes the speed of advancing bioanalytical measurements in a non-model organism. Moreover, proteomics may be a useful metrological tool to benchmark genome accuracy, though there is a need for reference proteomic datasets to facilitate this utility in new de novo and existing genomes."/> <meta name="og-type" property="og:type" content="article"/> <meta name="og-image" property="og:image" content="https://web.archive.org/web/20250130121542im_/https://www.biorxiv.org/sites/default/files/images/biorxiv_logo_homepage7-5-small.png"/> <meta name="citation_date" content="2018-02-02"/> <link rel="alternate" type="application/vnd.ms-powerpoint" title="Powerpoint" href="/web/20250130121542/https://www.biorxiv.org/content/10.1101/254250v1.ppt"/> <meta name="description" content="bioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution"/> <meta name="generator" content="Drupal 7 (http://drupal.org)"/> <link rel="canonical" 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class="region-inner region-content-inner"> <a id="main-content"></a> <div class="block block-system block-main block-system-main odd block-without-title" id="block-system-main"> <div class="block-inner clearfix"> <div class="content clearfix"> <div class="panel-display panels-960-layout jcore-2col-layout"> <div class="panel-row-wrapper clearfix"> <div class="main-content-wrapper grid-17 suffix-1 alpha"> <div class="panel-panel panel-region-content"> <div class="inside"><div class="panel-pane pane-highwire-article-citation"> <div class="pane-content"> <div class="highwire-article-citation highwire-citation-type-highwire-article node79377" data-node-nid="79377" id="node-79377--21865143979" data-pisa="biorxiv;254250v1" data-pisa-master="biorxiv;254250" data-apath="/biorxiv/early/2018/02/02/254250.atom" data-hw-author-tooltip-instance="highwire_author_tooltip"><div class="highwire-cite highwire-cite-highwire-article highwire-citation-biorxiv-article-top clearfix has-author-tooltip"> <span class="biorxiv-article-type"> New Results </span> <h1 class="highwire-cite-title" id="page-title">Proteomics as a metrological tool to evaluate genome annotation accuracy following <em>de novo</em> genome assembly: a case study using the Atlantic bottlenose dolphin (<em>Tursiops truncatus</em>)</h1> <div class="highwire-cite-authors"><span class="highwire-citation-authors"><span class="highwire-citation-author first hw-author-orcid-logo-wrapper" data-delta="0"><a href="https://web.archive.org/web/20250130121542/http://orcid.org/0000-0001-6120-7695" target="_blank" class="hw-author-orcid-logo link-icon-only link-icon"><span class="hw-icon-orcid hw-icon-color-orcid"></span> <span class="title element-invisible">View ORCID Profile</span></a><span class="nlm-given-names">Benjamin A.</span> <span class="nlm-surname">Neely</span></span>, <span class="highwire-citation-author" data-delta="1"><span class="nlm-given-names">Debra L.</span> <span class="nlm-surname">Ellisor</span></span>, <span class="highwire-citation-author" data-delta="2"><span class="nlm-given-names">W. Clay</span> <span class="nlm-surname">Davis</span></span></span></div> <div class="highwire-cite-metadata"><span class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">doi:</span> https://doi.org/10.1101/254250 </span></div> </div> <div id="hw-article-author-popups-node-79377--21865143979" style="display: none;"><div class="author-tooltip-0"><div class="author-tooltip-name">Benjamin A. Neely </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class="author-affiliation"><span class="nlm-sup">1</span><span class="nlm-institution">National Institute of Standards and Technology, Material Measurement Laboratory, Chemical Sciences Division, Marine Biochemical Sciences Group</span>, Hollings Marine Laboratory, 331 Fort Johnson Road, Charleston, SC 29412, <span class="nlm-country">United States</span></div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/web/20250130121542/https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Benjamin%2BA.%2BNeely%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/web/20250130121542/https://www.biorxiv.org/lookup/external-ref?access_num=Neely%20BA&link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/web/20250130121542/https://www.biorxiv.org/search/author1%3ABenjamin%2BA.%2BNeely%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link"><a href="https://web.archive.org/web/20250130121542/http://orcid.org/0000-0001-6120-7695" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for Benjamin A. Neely</a></li><li class="author-corresp-email-link last"><span>For correspondence: <a href="/web/20250130121542/https://www.biorxiv.org/cdn-cgi/l/email-protection#0567606b6f64686c6b2b6b6060697c456b6c76712b626a73" class="" data-icon-position="" data-hide-link-title="0"><span class="__cf_email__" data-cfemail="ea888f84808b878384c4848f8f8693aa8483999ec48d859c">[email protected]</span></a></span></li></ul></div><div class="author-tooltip-1"><div class="author-tooltip-name">Debra L. Ellisor </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class="author-affiliation"><span class="nlm-sup">2</span><span class="nlm-institution">National Institute of Standards and Technology, Material Measurement Laboratory, Chemical Sciences Division, Environmental Specimen Bank Group</span>, Hollings Marine Laboratory, 331 Fort Johnson Road, Charleston, SC 29412, <span class="nlm-country">United States</span></div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/web/20250130121542/https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Debra%2BL.%2BEllisor%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/web/20250130121542/https://www.biorxiv.org/lookup/external-ref?access_num=Ellisor%20DL&link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link last"><a href="/web/20250130121542/https://www.biorxiv.org/search/author1%3ADebra%2BL.%2BEllisor%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li></ul></div><div class="author-tooltip-2"><div class="author-tooltip-name">W. Clay Davis </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class="author-affiliation"><span class="nlm-sup">1</span><span class="nlm-institution">National Institute of Standards and Technology, Material Measurement Laboratory, Chemical Sciences Division, Marine Biochemical Sciences Group</span>, Hollings Marine Laboratory, 331 Fort Johnson Road, Charleston, SC 29412, <span class="nlm-country">United States</span></div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/web/20250130121542/https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=W.%2BClay%2BDavis%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/web/20250130121542/https://www.biorxiv.org/lookup/external-ref?access_num=Davis%20WC&link_type=AUTHORSEARCH" target="_blank" class="" 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alt="Loading" title="Loading"/></div><div class="panels-ajax-tab-wrap-biorxiv_tab_art"><div class="panel-display panel-1col clearfix"> <div class="panel-panel panel-col"> <div><div class="panel-pane pane-highwire-markup"> <div class="pane-content"> <div class="highwire-markup"><div xmlns="http://www.w3.org/1999/xhtml" data-highwire-cite-ref-tooltip-instance="highwire_reflinks_tooltip" class="content-block-markup" xmlns:xhtml="http://www.w3.org/1999/xhtml"><div class="article abstract-view "><span class="highwire-journal-article-marker-start"></span><div class="section abstract" id="abstract-1"><h2 class="">Abstract</h2><div id="sec-1" class="subsection"><p id="p-2"><strong>Background</strong> The last decade has witnessed dramatic improvements in whole-genome sequencing capabilities coupled to drastically decreased costs, leading to an inundation of high-quality <em>de novo</em> genomes. For this reason, continued development of genome quality metrics is imperative. The current study utilized the recently updated Atlantic bottlenose dolphin (<em>Tursiops truncatus)</em> genome and annotation to evaluate a proteomics-based metric of genome accuracy.</p></div><div id="sec-2" class="subsection"><p id="p-3"><strong>Results</strong> Proteomic analysis of six tissues provided experimental confirmation of 10 402 proteins from 4 711 protein groups, almost 1/3 of the possible predicted proteins in the genome. There was an increased median molecular weight and number of identified peptides per protein using the current <em>T. truncatus</em> annotation versus the previous annotation. Identification of larger proteins with more identified peptides implied reduced database fragmentation and improved gene annotation accuracy. A metric is proposed, NP10, that attempts to capture this quality improvement. When using the new <em>T. truncatus</em> genome there was a 21 % improvement in NP10. This metric was further demonstrated by using a publicly available proteomic data set to compare human genome annotations from 2004, 2013 and 2016, which had a 33 % improvement in NP10.</p></div><div id="sec-3" class="subsection"><p id="p-4"><strong>Conclusions</strong> These results demonstrate that new whole-genome sequencing techniques can rapidly generate high quality <em>de novo</em> genome assemblies and emphasizes the speed of advancing bioanalytical measurements in a non-model organism. Moreover, proteomics may be a useful metrological tool to benchmark genome accuracy, though there is a need for reference proteomic datasets to facilitate this utility in new <em>de novo</em> and existing genomes.</p></div></div><span class="highwire-journal-article-marker-end"></span></div><span class="related-urls"></span></div></div> </div> </div> <div class="panel-separator"></div><div class="panel-pane pane-biorxiv-copyright"> <div class="pane-content"> <div class="field field-name-field-highwire-copyright field-type-text field-label-inline clearfix"><div class="field-label">Copyright </div><div class="field-items"><div class="field-item even">The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.<span class="license-type"> This article is a US Government work. 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